Lead - Data Engineering

Designation: Team Lead - Data Engineering

Job Location: Remote

About Syngene: Syngene (www.syngeneintl.com) is an innovation-led contract research, development and manufacturing organization offering integrated scientific services from early discovery to commercial supply.

At Syngene, safety is at the heart of everything we do personally and professionally. Syngene has placed safety at par with business performance with shared responsibility and accountability, including following safety guidelines, procedures and SOPs, in letter and spirit

Key Responsibilities and Major Duties

• Support, maintain, and enhance PDS data products, ETL pipelines built using DBT, AWS Glue, Databricks, and other cloud-native technologies.
• Analyze, troubleshoot, and resolve production incidents, ensuring high availability, reliability, and adherence to service level agreements (SLAs).
• Develop pipeline enhancements, bug fixes, and operational automation to improve platform performance, scalability, and operational efficiency.
• Ensure data quality, integrity, and operational stability through validation, monitoring, root cause analysis, and proactive issue resolution.

• Familiarity and experience with Cloud infrastructure management and work closely with the Cloud engineering team

• Collaborate with Analytics Engineering, Cloud Engineering, and Business teams to support feature releases, production deployments, and continuous improvements.
• Develop and maintain monitoring, alerting, dashboards, and operational documentation to improve observability and enable efficient support.
• Stay current with modern data and AI technologies, including Databricks, Agentic AI, Retrieval-Augmented Generation (RAG), and AI-assisted development (Vibe Coding), and leverage them to drive operational excellence.

Core Technical Skills

• 3–5 years of experience in data engineering, production support, data operations or a related role.
• Hands-on experience with AWS Glue, Databricks, DBT and cloud-based data engineering services.
• Strong proficiency in SQL, Python and Apache Spark, with experience in debugging and performance optimization.
• Good understanding of ETL/ELT pipelines, data warehousing, data lakes and distributed data processing.
• Experience with data pipeline orchestration tools such as Apache Airflow, AWS Step Functions or Databricks Workflows.
• Experience with production monitoring, incident management, root cause analysis, SLA management and troubleshooting.
• Familiarity with data quality frameworks, validation processes and data reconciliation.
• Experience with version control systems such as Git or SVN and Agile development methodologies.

Cloud, Database & Operational Tools

• Familiarity with AWS services and data engineering technologies, including Amazon S3, Glue, Athena, Redshift and CloudWatch.
• Working knowledge of databases and query engines such as Redshift, PostgreSQL, Athena and other relational or analytical databases.
• Familiarity with operational and collaboration tools such as Jira, Confluence, ServiceNow.
• Understanding of CI/CD practices, deployment processes and production change management.
• Familiarity with monitoring and observability tools such as Grafana or equivalent platforms.

Additional Skills (Good to Have)

• Knowledge of data governance, access management, IAM, data security and compliance.
• Experience building reusable automation frameworks, self-healing pipelines or operational dashboards.
• Exposure to pharmaceutical or life sciences data platforms is an advantage.

Soft Skills

• Strong analytical thinking, problem-solving and debugging capabilities.
• Excellent communication and presentation skills, with the ability to explain technical issues and solutions to technical and non-technical stakeholders.
• Proactive attitude towards identifying operational improvements, automation opportunities and innovative solutions.
• Strong ownership, accountability and ability to work independently in a production support environment.
• Willingness to learn new technologies, adapt to evolving business requirements and collaborate across teams.
• Ability to prioritize multiple tasks, manage incidents effectively and work in a time-sensitive operational environment.

Equal Opportunity Employer:

It is the policy of Syngene to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by applicable legislation or local law. In addition, Syngene will provide reasonable accommodations for qualified individuals with disabilities.