Position: Engineering Manager -Data & Analytics Experience: 12-18 years Location: Pune, Mumbai, Chennai and Bangalore Required Skills: Experience: 12+ years of experience in data engineering, analytics, or related roles. Should have led at least 3 large legacy EDW/data platform modernization & migrations to snowflake/databricks/data on cloud engagements in the last 5+ years. Having experience in leading all aspects of the project/program life cycle, including strategy, roadmap, architecture, design, development, and Implementation for the multi-phase/multi-year engagements & rollouts. Experience with big data technologies (e.g., Hadoop, Spark, Kafka) and cloud platforms (e.g., AWS, Azure,Google Cloud). Technical Skills Lead large data platform modernization/migration engagements (Snowflake, Databricks). Strong understanding of data engineering concepts, including ETL processes, data warehousing, and data lakes. Hands-on experience with SQL, Python, or similar programming languages. Knowledge of data visualization tools (e.g., Tableau, Power BI) and advanced analytics solutions. Familiarity with data governance frameworks, GDPR, and data security best practices. Leadership & Communication: Excellent leadership skills with a proven ability to inspire and motivate teams. Strong problem-solving abilities and attention to detail. Outstanding communication and collaboration skills, with the ability to work across departments and levels of an organization. Good to have: Experience with AI/ML platforms and model deployment. Knowledge of real-time data processing and stream analytics. Prior experience in Agile methodologies and DevOps practices. Key Responsibilities: Data Infrastructure & Architecture: Design and implement scalable, robust, and secure data architectures that support analytics and data science workloads. Drive improvements in data quality, data governance, and data management practices. Collaborate with Cloud and DevOps teams to ensure data pipelines are optimized for performance and cost-efficiency, and automated testing. Team Leadership & Management: Lead, mentor, and manage a team of data engineers, QA, SM, analytics engineers, and data scientists. Conduct performance evaluations, provide feedback, and foster career growth within the team. Recruit and onboard new team members as needed. Project Management: Oversee the planning, execution, and delivery of data and analytics projects. Collaborate with Product, Data Science, and Business teams to understand project requirements and translate them into technical solutions. Ensure projects are completed on time, within scope, and with high-quality results. Innovation: Stay updated with the latest trends in big data, analytics, and AI technologies. Lead the adoption of best practices. Collaboration & Communication: Act as a liaison between engineering teams and business stakeholders, facilitating communication and ensuring alignment on project goals. Regularly report on project progress, risks, and issues to senior leadership.,
Employement Category:
Employement Type: Full timeIndustry: IT Services & ConsultingRole Category: Not SpecifiedFunctional Area: Not SpecifiedRole/Responsibilies: Engineering Manager -Data & Analytics