Assistant Manager- Data Engineer

Job Title: Assistant Manager - Data Engineer Location: Andheri (Mumbai) Job Type: Full-Time Department: IT Position Overview: The Assistant Manager - Data Engineer will play a pivotal role in the design, development, and maintenance of data pipelines that ensure the efficiency, scalability, and reliability of our data infrastructure. This role will involve optimizing and automating ETL/ELT processes, as well as developing and refining databases, data warehouses, and data lakes. As an Assistant Manager, you will also mentor junior engineers and collaborate closely with cross-functional teams to support business goals and drive data excellence. Key Responsibilities: Data Pipeline Development: Design, build, and maintain efficient, scalable, and reliable data pipelines to support data analytics, reporting, and business intelligence initiatives. Database and Data Warehouse Management: Develop, optimize, and manage databases, data warehouses, and data lakes to enhance data accessibility and business decision-making. ETL/ELT Optimization: Automate and optimize data extraction, transformation, and loading (ETL/ELT) processes, ensuring efficient data flow and improved system performance. Data Modeling & Architecture: Develop and maintain data models to enable structured data storage, analysis, and reporting in alignment with business needs. Workflow Management Systems: Implement, optimize, and maintain workflow management tools (e.g., Apache Airflow, Talend) to streamline data engineering tasks and improve operational efficiency. Team Leadership & Mentorship: Guide, mentor, and support junior data engineers to enhance their skills and contribute effectively to projects. Collaboration with Cross-Functional Teams: Work closely with data scientists, analysts, business stakeholders, and IT teams to understand requirements and deliver solutions that align with business objectives. Performance Optimization: Continuously monitor and optimize data pipelines and storage solutions to ensure maximum performance and cost efficiency. Documentation & Process Improvement: Create and maintain documentation for data models, workflows, and systems. Contribute to the continuous improvement of data engineering practices. Qualifications: Educational Background: B.E., B.Tech., MCA Professional Experience: At least 5 to 7 years of experience in a data engineering or similar role, with hands-on experience in building and optimizing data pipelines, ETL processes, and database management. Technical Skills: Proficiency in Python and SQL for data processing, transformation, and querying. Experience with modern data warehousing solutions (e.g., Amazon Redshift, Snowflake, Google BigQuery, Azure Data Lake). Strong background in data modeling (dimensional, relational, star/snowflake schema). Hands-on experience with ETL tools (e.g., Apache Airflow, Talend, Informatica) and workflow management systems . Familiarity with cloud platforms (AWS, Azure, Google Cloud) and distributed data processing frameworks (e.g., Apache Spark). Data Visualization & Exploration: Familiarity with data visualization tools (e.g., Tableau, Power BI) for analysis and reporting. Leadership Skills: Demonstrated ability to manage and mentor a team of junior data engineers while fostering a collaborative and innovative work environment. Problem-Solving & Analytical Skills: Strong analytical and troubleshooting skills with the ability to optimize complex data systems for performance and scalability. Experience in Pharma/Healthcare (preferred but not required): Knowledge of the pharmaceutical industry and experience with data in regulated environments Desired Skills: Familiarity with industry-specific data standards and regulations. Experience working with machine learning models or data science pipelines is a plus. Strong communication skills with the ability to present technical data to non-technical stakeholders. Why Join Us: Impactful Work: Contribute to the pharmaceutical industry by improving data-driven decisions that impact public health. Career Growth: Opportunities to develop professionally in a fast-growing industry and company. Collaborative Environment: Work with a dynamic and talented team of engineers, data scientists, and business stakeholders. Competitive Benefits: Competitive salary, health benefits and more. Show more Show less