Senior Data Engineer Job at Robert Half (Washington, DC)

Senior Data Engineer

Robert Half

Location:
United States , Washington, DC

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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Job Description:

I’m building a world-class team to power our next generation of data products. We’re looking for a Senior Data Engineer who knows AWS inside and out—someone who can design secure, scalable data pipelines, own ETL/ELT workflows, engineer cloud data infrastructure, and deliver dimensional and semantic models that our analysts, data scientists, and applications can trust. You’ll work closely with product, security, platform engineering, and analytics to move our architecture toward a real-time, governed, cost-aware, and highly automated data ecosystem.

Job Responsibility:

Design & build end-to-end pipelines on AWS (batch and streaming) using services like Glue, EMR, Lambda, Step Functions, Kinesis, MSK, and Fargate
Develop robust ETL/ELT (PySpark, Spark SQL, SQL, Python) for structured, semi-structured, and unstructured data at scale
Own data storage & processing layers: S3 (Lake/Lakehouse), Redshift (or Snowflake on AWS), DynamoDB, and Athena with strong partitioning, compaction, and performance tuning
Implement data models (3NF, dimensional/star, Data Vault, Lakehouse medallion) for analytics and operational workloads
Engineer secure infrastructure-as-code with Terraform (or CDK) across multi-account setups
implement CI/CD via GitHub Actions or AWS CodeBuild/CodePipeline
Harden security & governance: use IAM, Lake Formation, KMS, Secrets Manager, VPC/PrivateLink, GLUE Catalog, and fine-grained access controls
Partner with SecOps on compliance (e.g., SOC 2, FedRAMP, HIPAA depending on dataset)
Observability & reliability: build monitoring with CloudWatch, OpenTelemetry, and data quality checks (e.g., Great Expectations, Deequ), implement SLOs and alerts
Champion best practices: code reviews, testing (unit/integration), documentation, runbooks, and blameless postmortems
Mentor mid-level engineers and collaborate on architectural decisions, standards, and technical roadmaps

Requirements:

5–10+ years in data engineering
at least 3+ years deep on AWS
Hands-on with Spark/PySpark, distributed ETL, and data modeling for analytics (dimensional) and/or operational use
Strong command of SQL performance tuning, partitioning, file formats (Parquet/ORC/Avro), and cost/performance trade-offs
Proven security-first mindset: least privilege, secrets rotation, encryption at rest/in transit, network boundaries
Experience building production-grade data platforms with IaC and CI/CD
Excellent communicator who can translate business goals into data architecture

Nice to have:

Experience with Redshift RA3 tuning, Delta/Hudi/Iceberg, Data Mesh patterns, or dbt
Knowledge of ML feature stores (SageMaker Feature Store or equivalent)
Background in regulated environments (public sector, healthcare, financial services)
Active Public Trust or ability to obtain a clearance (preferred but not required)

What we offer:

medical
vision
dental
life and disability insurance
eligible to enroll in our company 401(k) plan

Additional Information:

Job Posted:
March 13, 2026

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