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Senior Datastage Developer Jobs in Washington (NOW HIRING)

Omm IT Solutions

Sr Data Engineer

Mclean, VA · On-site

$116K - $139K/yr

... focused Senior Data Engineer to help build and scale our cloud data platform. In this role, you ... IBM DataStage) to support modernization initiatives. \n * DevOps & CI\/CD: Familiarity with ...

Acumen Solutions

Data Analyst

Mclean, VA · On-site

... seeking a senior leadership position. Acumen Solutions employees are ambitious, committed ... Informatica, Pentaho, DataStage, Jitterbit, Mulesoft, etc. * Relevant IT certifications preferred ...

Acumen Solutions

Data Analyst

Mclean, VA · On-site

... seeking a senior leadership position. Acumen Solutions employees are ambitious, committed ... Informatica, Pentaho, DataStage, Jitterbit, Mulesoft, etc. * Relevant IT certifications preferred ...

Acumen Solutions

Data Analyst

Mclean, VA · On-site

... seeking a senior leadership position. Acumen Solutions employees are ambitious, committed ... Informatica, Pentaho, DataStage, Jitterbit, Mulesoft, etc. * Relevant IT certifications preferred ...

Acumen Solutions

Data Analyst

Mclean, VA · On-site

... seeking a senior leadership position. Acumen Solutions employees are ambitious, committed ... Informatica, Pentaho, DataStage, Jitterbit, Mulesoft, etc. * Relevant IT certifications preferred ...

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Senior Datastage Developer information

See Washington salary details

$16

$62

$86

How much do senior datastage developer jobs pay per hour?

As of Sep 3, 2026, the average hourly pay for senior datastage developer in Washington is $62.16, according to ZipRecruiter salary data. Most workers in this role earn between $52.02 and $84.95 per hour, depending on experience, location, and employer.

What is a senior Datastage developer?

A Senior Datastage Developer is an experienced IT professional who specializes in designing, developing, and maintaining ETL (Extract, Transform, Load) processes using IBM's Datastage tool. They work on integrating large volumes of data from various sources, ensuring data quality, and optimizing data workflows for business intelligence and analytics purposes. Senior Datastage Developers are responsible for troubleshooting complex data issues, mentoring junior developers, and collaborating with data architects and business stakeholders to deliver efficient data solutions.

What are the key skills and qualifications needed to thrive as a senior Datastage developer?

To thrive as a Senior Datastage Developer, you need advanced expertise in ETL processes, strong SQL skills, and experience with IBM DataStage, often supported by a degree in computer science or a related field. Familiarity with DataStage Designer, Director, and Administrator tools, as well as knowledge of data warehousing concepts and relevant certifications, is typically required. Strong analytical thinking, problem-solving abilities, and effective communication skills are crucial for collaborating with stakeholders and troubleshooting complex data integration issues. These competencies ensure efficient data pipeline development, high-quality data integration, and successful delivery of business intelligence solutions.

What are some common challenges faced by senior Datastage developers when working on large-scale ETL projects?

Senior Datastage Developers often encounter challenges such as optimizing ETL job performance, managing complex data transformations, and ensuring data quality across multiple sources. Balancing project timelines with the need for thorough testing and documentation is also common, given the critical nature of data integration tasks. Collaboration with data architects, business analysts, and QA teams is essential to address these challenges and deliver robust solutions that support organizational goals.

What is the difference between Senior Datastage Developer vs Data Warehouse Developer?

AspectSenior Datastage DeveloperData Warehouse Developer
CredentialsTypically requires experience with IBM DataStage, SQL, and possibly certifications in ETL toolsRequires SQL, data modeling, and ETL tool knowledge; certifications vary
Work EnvironmentFocuses on designing, developing, and maintaining ETL processes using DataStageDesigns and implements data warehouse solutions, including ETL, data modeling, and reporting
Industry UsageCommon in organizations using IBM DataStage for data integrationUsed across industries for building and managing data warehouses

The main difference is that a Senior Datastage Developer specializes in using IBM DataStage for ETL processes, while a Data Warehouse Developer has a broader role in designing and implementing entire data warehouse solutions, which may include various tools and techniques.

What are popular job titles related to Senior Datastage Developer jobs in Washington?

For Senior Datastage Developer jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Senior Datastage Developer jobs in Washington look for?

The top searched job categories for Senior Datastage Developer jobs in Washington are:

What are popular job titles related to Senior Datastage Developer jobs in WA?

For Senior Datastage Developer jobs in WA, the most frequently searched job titles are:

Senior Datastage Developer jobs near you
Infographic showing various Senior Datastage Developer job openings in Washington as of August 2026, with employment types broken down into 79% Full Time, 7% Part Time, and 14% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $129,288 per year, or $62.2 per hour.

Sr Data Engineer

Omm IT Solutions

Mclean, VA • On-site

$116K - $139K/yr

Contractor

Re-posted 20 days ago

Job description

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  • IT IS 100 % ON SITE POSITION IN Mc lean VA<\/b><\/span><\/span><\/span><\/span>
    <\/li>\n <\/ul>KEY REQUIRED SKILLS:<\/b><\/u><\/span><\/span>
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    • PySpark & Python for data pipeline development, Snowflake & AWS<\/b><\/span><\/span><\/span>
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      \n DESCRIPITION:<\/b><\/u>
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      \n We are seeking a hands\-on, delivery\-focused Senior Data Engineer to help build and scale our cloud data platform. In this role, you will design and develop modern data pipelines using PySpark, Snowflake, and AWS to optimize cloud data workloads. The ideal candidate combines strong engineering fundamentals with cloud\-native data expertise and is capable of translating complex business needs into robust, performant, and well\-documented data solutions. Experience within Fannie Mae, Freddie Mac, or equivalent GSE\/mortgage enterprise environments is highly valued.<\/span><\/span>
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      • Scalable Architecture<\/b>: Design and build scalable batch and streaming data pipelines using PySpark for large\-scale data processing.<\/span><\/span>
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      • Modernization<\/b>: Migrate legacy, on\-premises ETL workloads (e.g., IBM DataStage, Informatica) to high\-performing PySpark and Snowflake cloud pipelines.<\/span>
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      • Data Transformation<\/b>: Write production\-grade PySpark code to read from Amazon S3 (Parquet\/Delta files), execute complex transformations, and process massive datasets efficiently.
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      • Deduplication<\/b>: Design and implement robust deduplication strategies for high\-volume datasets using PySpark.
        Platform Engineering: Build and manage Snowflake warehouses, schemas, and data models optimized for enterprise analytics and business intelligence reporting.

        <\/b><\/span><\/span><\/span><\/li>\n
      • Iceberg Tables<\/b>: Design and implement Apache Iceberg tables in Snowflake to support open lakehouse architectures and data interoperability.
        Incremental Processing: Build and maintain Snowflake Dynamic Tables and Materialized Views to enable near real\-time analytics and query acceleration.

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      • PySpark Tuning<\/b>: Optimize distributed Spark jobs by leveraging partitioning, caching, broadcast joins, and shuffle optimization.
        Snowflake Optimization: Tune Snowflake workloads using clustering keys, micro\-partition pruning, query profiling, precise warehouse sizing, and strategic result caching.
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      • Cost Management:<\/b> Continuously monitor and optimize Spark jobs, Snowflake queries, and AWS infrastructure to balance speed and cloud expenditure.
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      • Data Quality:<\/b> Implement data validation, lineage tracking, and monitoring solutions across all pipeline stages to ensure high data integrity.
        Cross\-Functional Collaboration: Partner closely with data architects, business analysts, Technical Program Managers (TPMs), and corporate stakeholders to deliver dependable data products.

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      • Technical Documentation<\/b>: Author comprehensive technical designs, data schemas, and operational runbooks to ensure every pipeline is maintainable and audit\-ready.<\/span>
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        Requirements<\/h3>\n
        \n REQUIRED QUALIFICATION:<\/b><\/span><\/span><\/u>
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        • Experience: 6+ years of hands\-on data engineering experience in large\-scale enterprise environments.
          <\/span><\/span><\/span><\/li>\n
        • PySpark Expertise: Deep proficiency in building distributed data processing pipelines, handling S3 Parquet\/Delta files, and implementing complex transformations and deduplication logic.
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        • Snowflake Proficiency: Strong hands\-on experience with SnowSQL, Snowpipe, Streams, Tasks, and Role\-Based Access Control (RBAC). Proven track record establishing Iceberg tables, Dynamic Tables, and Materialized Views.
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        • AWS Cloud Ecosystem: Robust working knowledge of AWS services, including S3, Glue, EMR, Lambda, IAM, Step Functions, CloudWatch, and Redshift.
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        • Advanced SQL & Python: Mastery of advanced SQL techniques (window functions, CTEs, complex joins) alongside strong Python programming skills for automation, scripting, and orchestration utilities.
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        • Orchestration & Architecture: Solid understanding of data warehousing, ELT\/ETL patterns, data lakes, and lakehouse architectures using tools like Airflow or AWS Step Functions.
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        • Communication: Strong verbal and written communication skills with the ability to articulate technical decisions clearly to both technical peers and business leaders.<\/span><\/span>
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          \n PREFERRED QUALIFICATION:<\/b><\/span><\/u><\/span>
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          • Industry Experience: Prior experience working within heavily regulated environments such as financial services, mortgage banking, or GSE programs (Fannie Mae \/ Freddie Mac).
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          • ETL Migration: Hands\-on experience with legacy ETL frameworks (e.g., IBM DataStage) to support modernization initiatives.
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          • DevOps & CI\/CD: Familiarity with continuous integration and continuous deployment pipelines for data infrastructure (Git, Jenkins, GitHub Actions, Terraform).
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          • Data Quality Frameworks: Exposure to automated data quality and validation frameworks (e.g., Great Expectations, dbt testing suites).
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          • Streaming Analytics: Knowledge of real\-time streaming platforms like Apache Kafka or AWS Kinesis.
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          • Professional Certifications: AWS Certified Data Analytics, AWS Certified Solutions Architect, or SnowPro Core\/Advanced certifications.
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        Apply