About this role
Career Category Information Systems Job Description Role Description: Let’s do this. Let’s change the world. We are looking for highly motivated expert Data Engineer who can own the design & development of complex data pipelines, solutions and frameworks. The ideal candidate will be responsible to design, develop, and optimize data pipelines, data integration frameworks, and metadata-driven architectures that enable seamless data access and analytics. This role prefers deep expertise in big data processing, distributed computing, data modeling, and governance frameworks to support self-service analytics, AI-driven insights, and enterprise-wide data management. Roles & Responsibilities:
• Develop and maintain robust, scalable data pipelines using Databricks, Spark, and Delta Lake, enabling efficient batch and real-time processing. • Drive performance optimization efforts, including Spark tuning, resource utilization, job scheduling, and query improvements. • Identify and implement innovative solutions that streamline data ingestion, transformation, lineage tracking, and platform observability. • Build frameworks for metadata-driven data engineering, enabling reusability and consistency across pipelines. • Foster a culture of technical excellence, experimentation, and continuous improvement within the data engineering team. • Collaborate with platform, architecture, analytics, and governance teams to align platform enhancements with enterprise data strategy. • Partner with cross-functional teams to translate business needs into scalable, governed data products. • Mentor engineers across the team, promoting knowledge sharing and adoption of modern engineering patterns and tools. • Stay up to date with emerging data technologies and best practices, ensuring continuous improvement of Enterprise Data Fabric architectures. Must-Have Skills:
• Hands-on experience in data engineering technologies such as Databricks, PySpark, SparkSQL Apache Spark, AWS, Python, SQL, and Scaled Agile methodologies. • Proficiency in workflow orchestration, performance tuning on big data processing. • Strong understanding of AWS services • Experience with Data Fabric, Data Mesh, or similar enterprise-wide data architectures. • Ability to quickly learn, adapt and apply new technologies • Strong problem-solving and analytical skills • Excellent communication and teamwork skills • Experience with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices. Good-to-Have Skills:
• Good to have deep expertise in Biotech & Pharma industries • Experience in writing APIs to make the data available to the consumers • Experienced with SQL/NOSQL database, vector database for large language models • Experienced with data modeling and performance tuning for both OLAP and OLTP databases • Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops Education and Professional Certifications
• 4 to 7 years of experience in Computer Science, IT or related field • AWS Certified Data Engineer preferred • Databricks Certificate preferred • Scaled Agile SAFe certification preferred Soft Skills:
• Excellent analytical and troubleshooting skills. • Strong verbal and written communication skills • Ability to work effectively with global, virtual teams • High degree of initiative and self-motivation. • Ability to manage multiple priorities successfully. • Team-oriented, with a focus on achieving team goals. • Ability to learn quickly, be organized and detail oriented. • Strong presentation and public speaking skills.
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