Data Engineer

🔥 1 minute ago

🇺🇸 United States – Remote

💵 $131.3k - $237.3k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

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Leidos

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1969

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

Leidos is a leading systems integrator in science, technology, and engineering, providing solutions that transform and enable the missions of its customers. The company operates across various markets, including aviation, defense, energy, government, healthcare, intelligence, science, and space. Leidos is involved in AI, digital modernization, cyber operations, and integrated and mission software systems. With a commitment to diversity, equity, inclusion, and sustainability, Leidos also engages in charitable efforts and community enrichment programs. Additionally, it contributes to developing solutions for counter-unmanned aerial systems and electric vehicle infrastructure for military applications.

📋 Description

• Design logical and physical data models for analytical workloads • Develop data structures integrating multiple applications, databases, files, APIs, logs, and external sources • Evaluate data architectures and recommend improvements to reliability, scalability, performance, maintainability, and accessibility • Support data warehouses, data marts, data lakes, lakehouses, and other analytical repositories • Design, develop, test, deploy, and maintain ETL/ELT processes and automated data pipelines • Extract and integrate structured and semi-structured data from databases, applications, APIs, flat files, and logs • Transform raw transactional data into standardized, analysis-ready datasets • Implement pipeline scheduling, orchestration, monitoring, error handling, and recovery • Develop data feeds for reporting, dashboards, analytics platforms, and external systems • Clean, normalize, deduplicate, validate, and transform data • Investigate data discrepancies and determine root causes with technical and business teams • Implement data-quality controls • Develop curated datasets and models for BI, reporting, visualization, and analytics • Translate business questions into data requirements with BI analysts and stakeholders • Support enterprise metric and KPI definitions and ad hoc analytical requests • Assist analysts with data lineage, relationships, limitations, and appropriate use • Document data sources, transformations, interfaces, business rules, dependencies, lineage, and definitions • Maintain documentation for pipelines, models, interfaces, and analytical repositories • Support data dictionaries and metadata repositories • Develop and optimize SQL queries, stored procedures, views, and data transformations • Analyze and improve analytical query and data-processing performance • Work with DBAs to optimize database structures and recommend indexing, partitioning, aggregation, or caching • Ensure analytical workloads do not adversely affect production systems • Implement cybersecurity, privacy, access-control, classification, encryption, auditing, logging, retention, and protection requirements • Work with cybersecurity personnel on compliant data movement and storage • Protect sensitive information including PII and controlled or restricted data • Develop maintainable data-engineering code using software development practices • Maintain pipeline code and configuration under version control • Participate in peer reviews, testing, configuration management, and change control • Develop automated tests and support CI/CD and automated deployment • Troubleshoot production data-processing failures and perform root-cause analysis

🎯 Requirements

• Must be a U.S. Citizen • Must be capable of receiving a Public Trust clearance level • Must have verifiable accredited education • Bachelor's degree in Computer Science, Data Science, Information Systems, Software Engineering, Computer Engineering, Mathematics, Statistics, or a related technical discipline • 3–5+ years of professional experience in data engineering, database development, software engineering, BI engineering, or a related technical discipline • Demonstrated experience designing and developing ETL/ELT processes and data pipelines • Strong experience with relational databases and SQL • Experience integrating data from multiple heterogeneous sources • Experience developing analytical data models, data warehouses, or similar repositories • Experience troubleshooting data-quality and data-integration issues • Preferred experience with Azure, AWS, Snowflake, Databricks, Spark, Airflow, dbt, Kafka, Power BI, Tableau, or similar platforms • Strong proficiency in several of: advanced SQL and relational database concepts; Oracle, SQL Server, PostgreSQL, or comparable RDBMS technologies; Python or another data-processing/programming language; ETL/ELT development; data modeling and dimensional modeling; data warehouse architecture; REST APIs and system integration; data validation and quality management; Git or comparable version-control systems; automated testing and CI/CD concepts; structured and semi-structured data processing • Strong analytical and problem-solving skills • Ability to understand complex relationships among applications, databases, interfaces, and business processes • Ability to translate business information requirements into technical data solutions • Understanding of transactional versus analytical data architectures • Understanding of data lineage, governance, quality, security, and lifecycle management • Ability to communicate technical concepts to both technical and nontechnical audiences • Ability to distinguish between data, application, business-process, and analytical problems • Strong documentation and configuration-management discipline

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