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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