Des Moines, IA

Hire Data Engineer talent in Des Moines.

Data Engineer recruiting based on accountable delivery experience. Crosscheck recruits Data, Cloud & Security candidates for contract, contract-to-hire, and permanent roles tied to Des Moines.

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PracticeData, Cloud & Security
Search focusData Engineer · Des Moines
Photo by Brett Sayles on Pexels.
  • 48-hour target for qualified exclusive searches
  • 40-hour contract and 90-day permanent replacement terms

What We Place

Roles & Technologies

Representative roles

Data EngineerSenior Data EngineerETL EngineerStreaming Data EngineerData Engineering LeadData Pipeline Engineer

Platforms and technologies

SQLPythondbtAirflowSparkKafkaData WarehousesData Lakehousesdata ingestiontransformationstorageorchestrationqualitylineageaccessreliabilityand support for downstream usersData EngineerSenior Data EngineerETL EngineerStreaming Data EngineerData Engineering LeadData Pipeline Engineer

Our Approach

How we find Data Engineer talent in Des Moines.

This editorial hiring guide starts with sourced Des Moines business context. Des Moines' 2025 official statement lists major regional employers across financial services and insurance, health care and education, distribution, agricultural equipment, seed manufacturing, and other manufacturing. The list supplies current operating contexts without asserting open requisitions. A Data Engineer search should define the operating boundary before comparing resumes. The brief must distinguish Data Engineer, Senior Data Engineer, ETL Engineer and connect role-specific scope to the work this person will personally own. Screening centers on data ingestion, transformation, storage, orchestration, quality, lineage, access, reliability, and support for downstream users.

Define the systems, delivery stage, operating boundary, and ownership expected from the Data Engineer

Screen candidates for evidence of data ingestion, transformation, storage, orchestration, quality, lineage, access, reliability, and support for downstream users

Separate direct delivery experience from adjacent product, project, or consulting exposure

Support contract, contract-to-hire, and permanent searches across the US and Canada

Start the search

Tell us what your Data Engineer hire needs to own.

Include the business context, systems, delivery phase, work model, compensation, and interview timeline. A Crosscheck search lead will use that context to calibrate the role before sourcing begins.

Your Info
The Role
More detail = better candidates. Include stack, seniority, and any deal-breakers.
Preferences

A senior search lead reviews every brief and follows up about the next step.

Local Market Brief

Data Engineer hiring in Des Moines

Record the required decisions, systems, delivery stage, and support duties for Data Engineer work. Treat SQL, Python, dbt, Airflow as context for the assignment, not a keyword checklist. Separate that scope from adjacent Streaming Data Engineer, Data Engineering Lead, Data Pipeline Engineer responsibilities so each candidate is evaluated against the same completed brief. Build the calibration map from the actual assignment: Data Engineer against SQL and Python; Senior Data Engineer against dbt and Airflow; ETL Engineer against Spark and Kafka; Streaming Data Engineer against Data Warehouses and Data Lakehouses; Data Engineering Lead against data ingestion and transformation; Data Pipeline Engineer against storage and orchestration. For the delivery handoff, trace the working sequence from Kafka to Spark to Airflow to dbt to Python to SQL and name who accepts each boundary. The three sourced Des Moines contexts below turn that scope into intake and screening decisions. They do not measure current vacancies, candidate supply, or Crosscheck client activity.

Editorial market scenario

Name the domain constraint

Tie each must-have requirement to a task, system, risk, or deadline. Remove industry preferences that do not change how the person will perform the job. This is planning guidance, not measured local demand.

Editorial industry scenario

Finance and insurance systems

A finance-facing brief should identify the transaction, reporting, audit, privacy, and availability requirements attached to the role. Confirm that this context applies to the employer before using it in the search.

Screening focus

Stack and risk fit

Screening covers data scale, platform choices, governance needs, and the candidate's record of making data useful to downstream teams.

Published labor benchmark

Data Scientists in Des Moines-West Des Moines, IA

BLS does not publish an occupation matching Data Engineer. Crosscheck uses Data Scientists (15-2051) as the closest published broad benchmark; it is not a count or pay estimate for this exact specialty.

BLS OEWS May 2025, published May 15, 2026

Published metro employment

1,240

BLS publishes a narrower metro employment estimate for the proxy occupation. Screen for adjacent experience that transfers without lowering the production bar. The estimate equals 3.074 jobs per one thousand across the metro workforce.

Employment concentration

1.82 location quotient

Des Moines-West Des Moines, IA reports an above-national employment concentration for this proxy occupation. Confirm current availability through the active search.

Annual wage reference

$65,480 to $150,190

The metro median is 14% below the national Data Scientists median. Do not use the gap to discount niche platform or domain experience. BLS reports a $103,030 median for the proxy occupation in Des Moines-West Des Moines, IA.

Hiring brief scenarios

Build the Data Engineer brief around the work.

These scenarios connect location context to role responsibilities. Use them as prompts to verify with the employer, not as measures of Des Moines demand, clients, or candidate supply.

Sourced financial services and insurance context

Accounts, policies, and financial controls: Data Engineer

A September 2025 City of Des Moines official statement lists financial-services and insurance organizations among the metropolitan area's larger employers. Define how Spark, Kafka, Data Warehouses, Data Lakehouses fit the employer's current environment. Ask which constraints changed the design, what Data Engineer owned directly, who approved the decision, and how the result was checked after delivery. Financial and insurance systems can connect accounts, policies, premiums, claims, payments, identity, risk rules, approvals, reconciliations, statements, reporting, and audit evidence.

Evidence to request: Request a redacted design, configuration, test, runbook, review record, or operating measure that supports the candidate's account of Data Engineer ownership. Name the account, product, policy, transaction, or claim, source ledger, money movement, identity model, control owner, reconciliation, close or reporting date, and support obligation.

Sourced health care and education context

Protected care and learning records: Data Engineer

The same Des Moines document lists hospitals, clinics, a health-benefits firm, and public education among the metropolitan area's larger employers. Set the boundary for ownership checkpoints before interviews. A useful account involving data ingestion, transformation, storage, orchestration names the starting condition, alternatives considered, implementation sequence, failure handling, and the operating team that received the work. Health and education environments may join patient or student records, appointments, benefits, billing, learning systems, workforce data, access controls, retention, and reporting.

Evidence to request: Use a comparable scenario involving access, reliability, and support for downstream users, Data Engineer and score assumptions, technical judgment, communication, delivery steps, and the evidence proposed for acceptance. Set the care, benefits, teaching, or administrative workflow, authoritative record, protected data class, access reviewer, integration, reporting rule, retention requirement, and acceptance owner.

Sourced distribution and agricultural manufacturing context

Equipment, seed, freight, and inventory flow: Data Engineer

Des Moines' 2025 employer table also includes distribution and data-center work, farm equipment, seed manufacturing, package shipping, agricultural tires, and other manufacturing. Connect adjacent role boundaries to an employer decision rather than a broad tool list. Require the candidate to explain work with quality, lineage, access, reliability, including dependencies, controls, measurable evidence, and responsibility when the original plan changed. These operations can cross product engineering, seeds or materials, production, quality, equipment, warehouses, carriers, inventory, status events, delivery, and financial settlement.

Evidence to request: Ask for a problem involving Senior Data Engineer responsibilities. Record the signal, diagnosis, decision, corrective action, handoff, and verification the candidate personally completed. Choose the product or shipment, then trace its source specification, production or receipt, quality gate, serial or lot, inventory event, carrier handoff, delivery exception, settlement, and owner.

Interview scorecard

Three questions for this Des Moines search

Ask each candidate the same core questions. Score the evidence, ownership, and judgment in the answer instead of relying on job-title or keyword matches.

1. Data Engineer: SQL

Choose a SQL decision from your work as Data Engineer. Which constraint changed the design, and what evidence supported the result?

Use the answer to assess lineage, data quality, governed reporting, and recovery for business-critical pipelines. The finance and insurance systems context is an editorial scenario, not a measured claim about Des Moines.

2. Senior Data Engineer: Python

Describe project work you completed as Senior Data Engineer involving Python that did not follow the original plan. What did you own, and how did you correct it?

Use the answer to assess lineage, data quality, governed reporting, and recovery for business-critical pipelines. The finance and insurance systems context is an editorial scenario, not a measured claim about Des Moines.

3. ETL Engineer: dbt

For a dbt system you supported, explain the handoff, operating limits, and measures used after launch. Where did your responsibility begin and end?

Use the answer to assess lineage, data quality, governed reporting, and recovery for business-critical pipelines. The finance and insurance systems context is an editorial scenario, not a measured claim about Des Moines.

Open the Data Engineer technical evaluation guide

Data Engineer: Role-specific scope

Screened for data ingestion, transformation, storage, orchestration, quality, lineage, access, reliability, and support for downstream users, with the boundary set by the employer's systems, delivery stage, and operating model. The evaluation connects SQL, Python, dbt to a concrete hiring responsibility.

Show how SQL, Python, dbt shaped one delivery decision. Which constraint mattered, and what did the candidate own?

Evidence check: Look for an artifact, test, configuration record, or operating measure that supports the account. Compare it with work such as technical product and platform teams.

Senior Data Engineer: Role-specific scope

Screened for data ingestion, transformation, storage, orchestration, quality, lineage, access, reliability, and support for downstream users, with the boundary set by the employer's systems, delivery stage, and operating model. The evaluation connects Airflow, Spark, Kafka to a concrete hiring responsibility.

Where did Senior Data Engineer work involving Airflow, Spark, Kafka fail or change direction? What evidence prompted the correction?

Evidence check: A useful answer names the failure signal, the candidate's decision, and the result. Certification alone does not establish project ownership.

ETL Engineer: Role-specific scope

Screened for data ingestion, transformation, storage, orchestration, quality, lineage, access, reliability, and support for downstream users, with the boundary set by the employer's systems, delivery stage, and operating model. The evaluation connects Data Warehouses, Data Lakehouses, data ingestion to a concrete hiring responsibility.

Explain the handoff and operating boundary for a project using Data Warehouses, Data Lakehouses, data ingestion. Who approved changes, monitored results, and supported the system?

Evidence check: Request documentation, controls, or production measures that distinguish direct ownership from observation or team-level credit.

Streaming Data Engineer: Ownership checkpoints

Screened for data ingestion, transformation, storage, orchestration, quality, lineage, access, reliability, and support for downstream users, with the boundary set by the employer's systems, delivery stage, and operating model. The evaluation connects transformation, storage, orchestration to a concrete hiring responsibility.

Which tradeoff would change the design of transformation, storage, orchestration for this hiring task: support contract, contract-to-hire, and permanent searches across the us and canada?

Evidence check: Score the response on technical judgment, stated assumptions, and evidence from comparable work rather than vocabulary coverage.

Who We Work With

Hiring context in Des Moines.

Organizations hiring across Des Moines can use the market context below to shape location, compensation, and screening requirements for Data Engineer searches.

Technical product and platform teams

Transformation and implementation programs

Internal engineering and operations teams

Systems integration and advisory teams

Crosscheck recruiting workflow

A structured search,
managed in one workflow.

TalentCube is Crosscheck Staffing's internal recruiting workflow. Recruiters use it to organize hiring briefs, sourcing activity, and screening notes. A profile is not treated as an available candidate until a recruiter confirms interest and fit during an active search.

Learn About TalentCube

Hiring Brief

Records role scope, work model, and interview requirements.

Search Workspace

Keeps sourcing activity connected to the agreed brief.

Screening Notes

Documents role evidence for recruiter review.

Recruiter Verification

Interest and availability are confirmed during the active search.

FAQ

Common questions about Data Engineer recruiting in Des Moines.

What should employers know about the Data Engineer market in Des Moines?

Record the required decisions, systems, delivery stage, and support duties for Data Engineer work. Treat SQL, Python, dbt, Airflow as context for the assignment, not a keyword checklist. Separate that scope from adjacent Streaming Data Engineer, Data Engineering Lead, Data Pipeline Engineer responsibilities so each candidate is evaluated against the same completed brief. Build the calibration map from the actual assignment: Data Engineer against SQL and Python; Senior Data Engineer against dbt and Airflow; ETL Engineer against Spark and Kafka; Streaming Data Engineer against Data Warehouses and Data Lakehouses; Data Engineering Lead against data ingestion and transformation; Data Pipeline Engineer against storage and orchestration. For the delivery handoff, trace the working sequence from Kafka to Spark to Airflow to dbt to Python to SQL and name who accepts each boundary. The three sourced Des Moines contexts below turn that scope into intake and screening decisions. They do not measure current vacancies, candidate supply, or Crosscheck client activity. Start the intake with Accounts, policies, and financial controls: Data Engineer. Request a redacted design, configuration, test, runbook, review record, or operating measure that supports the candidate's account of Data Engineer ownership. Name the account, product, policy, transaction, or claim, source ledger, money movement, identity model, control owner, reconciliation, close or reporting date, and support obligation.

Which Data Engineer experience matters most to hiring teams in Des Moines?

Screening covers data scale, platform choices, governance needs, and the candidate's record of making data useful to downstream teams. Apply the same evidence standard regardless of whether the role is on-site, hybrid, or remote. Request a redacted design, configuration, test, runbook, review record, or operating measure that supports the candidate's account of Data Engineer ownership. Name the account, product, policy, transaction, or claim, source ledger, money movement, identity model, control owner, reconciliation, close or reporting date, and support obligation.

Is Crosscheck's Des Moines market description a measured local forecast?

No. The a insurtech and fintech hub label is an internal editorial scenario used to organize intake questions. It does not measure current vacancies, candidate supply, local clients, or Crosscheck placements. Tie each must-have requirement to a task, system, risk, or deadline. Remove industry preferences that do not change how the person will perform the job. The same Des Moines document lists hospitals, clinics, a health-benefits firm, and public education among the metropolitan area's larger employers. Set the boundary for ownership checkpoints before interviews. A useful account involving data ingestion, transformation, storage, orchestration names the starting condition, alternatives considered, implementation sequence, failure handling, and the operating team that received the work. Health and education environments may join patient or student records, appointments, benefits, billing, learning systems, workforce data, access controls, retention, and reporting.

Can Crosscheck recruit Data Engineer candidates beyond Des Moines?

Use the stated location as the starting point and widen the search only when the work model supports it. Recruiters evaluate introduced candidates against the same role, delivery, and technical requirements. Ask for a problem involving Senior Data Engineer responsibilities. Record the signal, diagnosis, decision, corrective action, handoff, and verification the candidate personally completed. Choose the product or shipment, then trace its source specification, production or receipt, quality gate, serial or lot, inventory event, carrier handoff, delivery exception, settlement, and owner.

Can Crosscheck recruit Data Engineer candidates outside Des Moines?

Yes. Crosscheck supports on-site, hybrid, and remote searches across the US and Canada, subject to the employer's location and work-authorization requirements.

Do you recruit Data Engineer professionals for contract and permanent roles?

Yes. Crosscheck supports contract, contract-to-hire, and permanent searches. Permanent placements include a 90-day replacement guarantee, subject to the signed agreement.

Ready to hire your next Data Engineer in Des Moines?

For qualified exclusive searches in our core disciplines, Crosscheck targets a first candidate slate within 48 hours after a completed intake. Contract placements include a 40-billable-hour replacement guarantee, and permanent placements include a 90-day replacement guarantee, subject to the signed agreement.

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