Senior Data Engineer

• Leverage enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous improvement
• Evaluate emerging trends to inform solution design and strategic innovation
• Design, develop, and maintain secure, scalable, and robust data pipelines using Azure Databricks, Python, and Apache Spark
• Extract, transform, and load (ETL) data from legacy platforms like Teradata and IBM DataStage into modern cloud-based data environments
• Orchestrate and schedule complex data workflows and ETL processes using orchestration tools (with a preference for Apache Airflow)
• Optimize data pipeline performance, troubleshooting bottlenecks, and ensuring data quality and integrity
• Collaborate with cross-functional teams to translate business and data requirements into efficient engineering solutions
• Provide technical guidance, mentoring, and support to junior engineers within the team
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:

• Bachelor's/master's degree (such as B.E, B. Tech, MCA, M. Tech, MS) in Computer Science, Information Technology, or a related field, or equivalent work experience (such as 4+ years of software/data development experience in lieu of a degree)
• 3+ years of professional experience in data engineering, database management, or software engineering
• 3+ years of experience designing and developing data pipelines using Apache Spark (PySpark or Scala) and Python
• 2+ years of experience building and optimizing modern cloud data solutions using Azure Databricks
• 2+ years of experience migrating or integrating legacy ETL platforms (such as IBM DataStage) and databases (such as Teradata)
• 1+ years of experience with workflow scheduling/orchestration tools (such as Apache Airflow, Autosys, or equivalent)
• Proven communication and presentation skills, with the ability to articulate technical details to stakeholders

Preferred Qualifications:

• Experience building and orchestrating data integrations using Azure Data Factory
• Hands-on experience utilizing generative AI tools (such as GitHub Copilot) to accelerate coding, unit testing, and documentation
• Experience writing and optimizing Unix Shell or Perl scripts
• Experience leading or mentoring a team of junior engineers
  • Knowledge of healthcare domain datasets, particularly around Customer, Member, Claims, and Provider information