Senior Data Engineer

SteerBridge

. Align data solutions to business requirements by planning and managing data infrastructure and strategy for the Modern Disability Claims AI/ML program.

Posted 9/18/2026full-timeVienna • Virginia • United StatesSenior💰 $135,000 - $160,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in data engineering, including building and managing cloud-native data solutions, optimizing data pipelines, and implementing data governance frameworks. Proficient in Python, SQL, and advanced data modeling techniques to support analytics and machine learning workflows.

Highest-signal resume keywords

Data Pipeline DevelopmentCloud-Native Data SolutionsPython ProgrammingData Governance ImplementationAdvanced Data Modeling

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

PythonSQLData Pipeline AutomationData ModelingETL WorkflowsData Quality ChecksCloud Storage SolutionsData CatalogingAdvanced Analytics ToolsData Versioning

Soft Skills

MentoringTechnical DocumentationCollaborationLeadershipAgile Project Management

Tools & Technologies

AWS GlueGCP DataflowAzure Data FactoryApache KafkaAirflowSparkTableauPower BIGitLabDocker

Certifications & Qualifications

Public Trust ClearanceSecret ClearanceTop Secret Clearance

Industry Keywords

Data GovernanceGDPR ComplianceCCPA ComplianceOLTPOLAPNoSQL DatabasesData LakesData WarehousesMachine LearningData Privacy

Tech Stack

Tools & technologies

AirflowAmazon RedshiftApacheAWSAzureBigQueryCloudDistributed SystemsDockerETLGoogle Cloud PlatformHadoopJenkinsKafkaKubernetesNoSQLNumpyPandasPySparkPythonPyTorchRayScikit-LearnSparkSQLTableauTensorflow

About the role

Key responsibilities & impact

Align data solutions to business requirements by planning and managing data infrastructure and strategy for the Modern Disability Claims AI/ML program.
Perform data engineering tasks within existing systems of record and multiple databases.
Enhance and optimize data entry, management, and extraction for use within SteerBridge’s proprietary system.
Perform data quality checks and analysis.
Present data and document data management processes.
Design and implement scalable, maintainable data models for analytics, reporting, and ML workflows.
Build and orchestrate fault-tolerant, high-throughput batch and real-time data pipelines.
Implement pipeline automation, observability, monitoring, retries, and failure recovery.
Build and manage cloud-native data lakes, warehouses, and mesh solutions.
Migrate legacy ETL workflows and data systems to cloud-native architectures.
Build and maintain large-scale data platforms for structured and unstructured data.
Optimize queries, schemas, databases, distributed systems, pipeline efficiency, and resource utilization.
Implement data governance, lineage, access control, privacy, compliance, and security policies.
Collaborate with data scientists on feature engineering, data preparation, model deployment, and ML-ready infrastructure.
Mentor junior engineers and lead cross-functional data initiatives.
Promote data engineering and governance best practices.
Conduct technical reviews and enforce design and scalability standards.

Requirements

What you’ll need

Must be a U.S. Citizen.
Bachelor's Degree or Above in Systems Engineering, Computer Science, or related field.
Must hold, or be able to obtain, a Public Trust clearance; an active Secret or Top Secret clearance also satisfies this requirement.
Minimum 6+ years of experience.
Experience in data pipelines, advanced analytics tools and platforms, and Python.
Experience in scripting, tooling, and automating large-scale computing environments.
Extensive experience with Python, Pandas, PySpark, NumPy, SciPy, SQL, and Git.
Minor experience with TensorFlow, PyTorch, and Scikit-learn.
Advanced conceptual, logical, and physical data modeling.
Understanding of relational, NoSQL, graph, time-series, and document-based databases.
Expertise with Redshift, Snowflake, or BigQuery.
Experience with OLTP and OLAP workloads, schema evolution, metadata-driven pipelines, and data versioning.
Experience with Apache Kafka, Airflow, Spark, Flink, and NiFi.
Experience building batch and real-time pipelines using AWS Glue, GCP Dataflow, or Azure Data Factory.
Expertise in AWS, GCP, or Azure data ecosystems and cloud-native data solutions.
Experience with cloud storage, managed databases, compute services, hybrid/multi-cloud architecture, and inter-cloud data movement.
Experience with Hadoop, Spark, Hive, Presto, Delta Lake, Apache Iceberg, or Apache Hudi.
Advanced SQL/NoSQL query tuning, indexing, sharding, partitioning, replication, backups, and disaster recovery.
Experience implementing GDPR/CCPA privacy and compliance frameworks.
Experience with data cataloging, lineage, metadata management, RBAC, sensitive data protection, and CI/CD data quality validation.
Strong Python and SQL proficiency, OOP, design patterns, algorithmic complexity, and performance optimization.
Familiarity with Spark, Dask, Ray, MLflow, Kubeflow, and feature stores.
Experience with Tableau or Power BI.
Experience with GitLab, Jenkins, CircleCI, pytest/unittest, Docker/Kubernetes, infrastructure as code, and automated deployment.
Ability to mentor junior engineers, lead cross-functional projects, conduct technical reviews, and manage Agile projects.
Strong technical documentation skills using Lucidchart, PlantUML, or Draw.io.

Benefits

Comp & perks

Health insurance
Dental insurance
Vision insurance
Life Insurance
401(k) Retirement Plan with matching
Paid Time Off
Paid Federal Holidays