Senior Backend Software Engineer (supporting NOAA)

ASRC Federal•Silver Spring, MD

6d•Remote

About The Position

ASRC Federal is seeking a Senior Backend Software Engineer to support NOAA in a remote, full-time position. The role designs, develops, and optimizes data pipelines and database backends that support applications. It focuses on Java ETL workflows, ORM-based data access using Java persistence frameworks, SQL and relational database performance, backend services, and API development for data integration, processing, and retrieval. The engineer builds reliable, scalable systems and troubleshoots performance across Java application code, ORM-generated queries, and relational databases. The role also works with search platforms and AWS-hosted Amazon Aurora, monitors production pipeline and query performance, creates automated tests, and collaborates with engineers and stakeholders on requirements and design. Education: BS/BA degree (or equivalent) plus 8–10 years of experience in a related field.

Requirements

Strong Java development experience building and supporting production backend applications.
Demonstrated experience designing, developing, and maintaining ETL pipelines and data integration workflows.
Hands-on experience with Java Spring ORM and persistence frameworks such as JPA/Hibernate.
Experience writing and optimizing JPQL and SQL queries, including troubleshooting ORM-generated SQL.
Strong SQL proficiency, including complex joins, common table expressions, window functions, aggregations, and set-based processing.
Experience analyzing database execution plans and improving query performance through indexing and query changes.
Experience with relational data modeling, schema migrations, entity relationships, and transaction management.
Understanding of database isolation levels, locking, and concurrency.
Experience implementing data validation, incremental processing, error handling, and recoverable data workflows.
Experience with version control, code review, automated testing, and software deployment practices.
Ability to explain production performance improvements using measured results.
BS/BA degree or equivalent, plus 8–10 years of experience in a related field.

Nice To Haves

Experience with workflow orchestration, job scheduling, change data capture, and pipeline monitoring.
Experience diagnosing ORM performance issues such as N+1 queries, inefficient relationship loading, and excessive entity loading.
Experience processing large datasets within defined delivery windows while managing database resource utilization.
Familiarity with Apache Spark for ETL and distributed data processing.

Responsibilities

Design, develop, and maintain Java-based ETL workflows that extract, transform, validate, and load data from databases, APIs, files, and other source systems.
Implement data cleansing, transformation, deduplication, and reconciliation to ensure accurate and consistent downstream data.
Develop incremental loading, batching, retry, and recovery processes that support reliable execution and safe reprocessing without duplicate records.
Build and maintain ORM-based data access layers using Java persistence frameworks such as JPA/Hibernate, including entity mappings, relationships, and transaction management.
Develop and optimize SQL queries supporting application functionality and data processing.
Inspect SQL generated by JPA/Hibernate in Spring applications and analyze database execution plans to identify performance bottlenecks.
Improve database performance through indexing, query restructuring, batching, pagination, and relationship-loading strategies.
Design and maintain relational schemas, constraints, indexes, and versioned database migrations.
Select ORM operations, parameterized SQL, or database-native bulk operations based on workload, maintainability, and performance requirements.
Implement and optimize OpenSearch or Elasticsearch queries, filters, and aggregations; troubleshoot search performance and maintain consistency between source data and search indexes.
Monitor pipeline reliability, data quality, processing throughput, and query response times; troubleshoot production issues and demonstrate measurable improvements.
Create automated tests for transformation logic, database interactions, data integrity, and recovery behavior.
Collaborate with engineers and stakeholders to define requirements, document data mappings, and review database and pipeline designs.
Design, develop, and maintain GraphQL APIs and resolvers for efficient data retrieval and integration with backend services and relational databases.
Develop and optimize database integrations using Amazon Aurora within Amazon RDS in AWS, including connection management, schema migrations, ETL workflows, and query performance tuning.