Why this role stands out
Take your career to the next level at SAIC by building cutting-edge data pipelines in a supportive, collaborative environment that offers the perfect balance of professional growth and hybrid flexibility. If you are a technical expert passionate about AWS and Databricks, this role provides the ideal platform to make a significant impact on complex data architecture projects. Apply today to join a team that values your advanced expertise and drive for innovation.
Quick overview
Job description
Position Overview
We are seeking a AWS Databricks Developer to build and maintain scalable data pipelines on AWS. This role will turn data from databases, APIs, and files into reliable datasets for analytics and business reporting.
Responsibilities:
Develop batch and incremental ETL/ELT pipelines using Databricks, PySpark, Spark SQL, and Delta Lake.
Build and maintain Bronze, Silver, and Gold data layers using Medallion Architecture.
Ingest and transform structured and semi-structured data from sources such as Oracle, SQL Server, REST APIs, and Amazon S3.
Implement data quality checks, including schema validation, deduplication, reconciliation, and business rule enforcement.
Optimize Spark jobs and Delta tables to improve processing time and control cloud resource use.
Publish curated datasets to Amazon Redshift and support reporting in Power BI, Tableau, or Amazon QuickSight.
Orchestrate, monitor, and troubleshoot production pipelines using Databricks Workflows, Apache Airflow, and AWS monitoring services.
Collaborate with analysts, architects, QA, and DevOps teams on requirements, releases, and production support.
Required Qualifications:
Master's Degree in technical domain required.
5+ years of overall technology experience.
3+ years of AWS engineering experience.
Strong Python and SQL skills, with hands-on experience in PySpark, Databricks, and Delta Lake.
Experience building data pipelines on AWS, particularly with Amazon S3, AWS Glue, and Amazon Redshift.
Knowledge of incremental loading, dimensional data modeling, data quality practices, and Spark performance tuning.
Experience with Git, CI/CD workflows, and Agile delivery.
Preferred Qualifications:
Experience with Databricks Auto Loader, Unity Catalog, and AWS Glue Data Catalog.
Experience supporting manufacturing, supply chain, quality, or operational analytics.
Databricks Certified Data Engineer Associate and AWS Certified Data Engineer Associate certification.
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