Data Engineer

Description

The company supports US federal agencies across defense, national security, public safety, civilian and military health work.

It is a technology firm inside a larger global consulting group, with more than 13,000 staff and a Glassdoor Top 100 Best Place to Work ranking.

The team focuses on data platforms that feed analytics, reporting and machine learning work for federal missions.

Responsibilities

• Build and run batch and streaming data pipelines that serve analytics and AI workloads.
• Pull structured, semi-structured and unstructured data from APIs, databases, SaaS systems, streams and files.
• Clean, enrich, standardize and transform data with Dataflow (Apache Beam), Dataproc (Spark), BigQuery SQL and Python.
• Load curated, high-quality datasets into BigQuery for analytics, reporting and model training.
• Build and maintain feature pipelines that are ready for ML use, supporting data scientists and ML engineers.
• Add data quality checks, schema validation and automated tests inside pipelines.
• Monitor pipeline health with Cloud Monitoring and Cloud Logging.
• Apply IAM, encryption, data masking and auditing to meet governance, security and compliance standards.
• Manage schema changes, metadata and lineage with Dataplex or Data Catalog.
• Document datasets, transformations, pipeline logic and operating procedures.
• Write efficient, maintainable Python, SQL, Beam and Spark code.
• Manage ingestion through Pub/Sub, GCS, APIs, Datastream and database connectors.
• Tune BigQuery tables, partitions, clustering, materialized views and query speed.
• Build and maintain DAGs in Cloud Composer (Airflow).
• Diagnose pipeline failures, latency problems and data quality gaps.
• Take part in code reviews, architecture discussions and agile sprint ceremonies.
• Work with data architects, data scientists, ML engineers and business stakeholders.
• Build and maintain infrastructure as code in Terraform and CI/CD deployment pipelines.

Requirements

• You must be a U.S. citizen able to obtain a Public Trust clearance.
• A bachelor's degree in computer science, software engineering, information systems, data engineering or a related technical field.
• 3 to 6+ years of hands-on data engineering or closely related technical experience.
• At least 3 years of leading technical teams to deliver results.
• Experience setting and implementing technical standards for cloud and on-premises environments.
• Proven record of running production data pipelines on cloud platforms, preferably GCP.
• Hands-on work with BigQuery, GCS, Dataflow (Apache Beam), Dataproc (Spark) and Pub/Sub.
• Experience preparing ML-ready datasets for model training.
• Strong skills in SQL, Python, distributed data processing and data modeling.
• Experience with governance, security and compliance frameworks, including IAM, encryption, data masking and auditing.
• Familiarity with VAEC operational tools: Google Cloud security, monitoring and logging, networking, and storage services.

Conditions

The company posts pay ranges for roles in listed states as required by local law, based on labor costs in those locations.

Pay depends on location, role, skill set and experience level.

Applications are accepted on an ongoing basis with no fixed deadline.

Base pay range for this role in those listed locations: $103,200 to $196,400 USD.

The company is committed to equal opportunity and an inclusive workplace.

Benefits

• A wide range of benefits is offered.
• Support for growth through hands-on experience, certifications and industry training.