Data Analytics Engineer

About the role

Design, develop, and support scalable enterprise data pipelines for reporting, analytics, and business applications. Build and optimize cloud-based data solutions by integrating information from various enterprise data sources. Develop and maintain modern data platforms using Databricks, Spark technologies, and cloud data engineering best practices. Partner with application developers, analysts, and business stakeholders to create reusable data products and support business-critical applications. Implement data quality controls, monitoring, metadata management, and documentation to ensure trusted data assets. Participate in Agile delivery, solution design, CI/CD processes, and continuous improvement initiatives across the data ecosystem.

Requirements

• 3–7 years of experience in Data Engineering, Analytics Engineering, or Software Development with a focus on enterprise data solutions.
• Strong experience designing and developing ETL/ELT pipelines, data integration frameworks, and cloud-based data platforms.
• Hands-on experience with Databricks, including PySpark, Spark SQL, Delta Lake, and modern lakehouse architectures.
• Experience building data ingestion pipelines using tools like Azure Data Factory, APIs, SQL databases, or Kafka.
• Strong programming experience with Python and SQL, along with knowledge of relational databases and data warehousing concepts.
• Experience with source control and DevOps tools such as GitHub and Azure DevOps, including CI/CD best practices.

Benefits

• Opportunity to work on long-term contract projects.
• Hybrid work model with a presence in Atlanta, GA.
• Engage in designing and optimizing advanced cloud-based data solutions.
• Work with cutting-edge technologies like Databricks, Spark, and Azure.