Mgr Data Engineer - Research Data and Analytics

Location: Prakāshamnagar

In this vital role, you will create and develop data lake solutions for scientific data that drive business decisions for Research. You will build scalable and high-performance data engineering solutions for large scientific datasets and collaborate with Research partners. The ideal candidate possesses deep technical skills, is proficient with big data technologies, and has a deep understanding of data architecture and  ETL  processes.

You will also provide technical leadership and mentorship to junior team members.

Roles & Responsibilities     Team Leadership & Mentorship:  Lead, manage, and mentor a high-performing team of data engineers, fostering their development and ensuring adherence to best practices.
Data Pipeline Development:  Design, develop, and implement data pipelines,  ETL  processes, and data integration solutions. You will take ownership of data pipeline projects from inception to deployment, managing scope, timelines, and risks.
Data Modeling & Optimization:  Develop and maintain data models for biopharma scientific data, data dictionaries, and other documentation to ensure data accuracy and consistency. You will also optimize large datasets for query performance.
Collaboration & Solution Design:  Collaborate with global cross-functional teams, including research scientists, Data Architects, Business  SMEs , Software Engineers, and Data Scientists, to understand data requirements and design end-to-end solutions that meet fast-paced business needs.
Security & Compliance:  Implement data security and privacy measures to protect sensitive data.
Innovation & Process Improvement:  Explore new tools and technologies to improve  ETL  platform performance. You will identify and resolve data-related challenges and adhere to best practices for coding, testing, and designing reusable components.
Technical Skills    Proficiency in  SQL  and  Python  for data engineering, test automation frameworks ( pytest ), and scripting tasks.
Hands-on experience with  big data technologies  and platforms, such as  Databricks  and  Apache Spark  ( PySpark, Spark

SQL ).
Expertise in workflow orchestration and performance tuning on big data processing.
Good understanding of  data modeling, data warehousing , and  data integration  concepts.
Knowledge of  cloud data platforms  ( AWS  preferred).
Experience using  RDBMS  (e.g., Oracle, MySQL, SQL Server, Postgre

SQL) is a plus.

Experience with data visualization tools (e.g., Dash, Plotly, Spotfire) is a plus.

Experience with diagramming and collaboration tools such as  Miro  or  Lucidchart  is a plus.
Understanding of data governance frameworks, tools, and best practices is a plus.
Databricks Certified Data Engineer Professional  certification is preferred.
Qualifications    A Doctorate Degree, or a Master's degree with relevant experience, or a Bachelor's degree with extensive experience, or a Diploma with a substantial background in Computer Science, IT, Computational Chemistry, Computational Biology/Bioinformatics, or a related field.
Experience in implementing and supporting biopharma scientific research data analytics (software platforms) is preferred.
Soft Skills     Problem-Solving:  Excellent critical-thinking and problem-solving skills, with the ability to work with large, complex datasets.
Communication:  Good communication and collaboration skills, with demonstrated presentation abilities.
Leadership:  Ability to engage with business stakeholders and mentor teams to develop data pipelines and data models.
Proactiveness:  A passion for tackling complex challenges in drug discovery with technology and data.