Engineering Manager

As a DE Manager, you will be responsible for:

• Leading a team of talented data engineers responsible for designing, building, and maintaining scalable data pipelines and infrastructure
• Work closely with cross-functional teams to ensure client data systems meet the highest standards of quality and performance
• Lead, mentor, and develop a team of data engineers, fostering a collaborative and inclusive team environment
• Conduct regular performance reviews, provide feedback, and set goals for team members
• Identify and address skill gaps, and provide opportunities for professional development
• Plan, execute, and deliver data engineering projects on time and within scope
• Coordinate with stakeholders to gather requirements, set priorities, and define project timelines.
• Ensure projects align with overall business objectives and data strategy
• Oversee the design, development, and maintenance of data pipelines, ETL processes, and data warehouse
• Ensure data quality, integrity, and security across all data engineering projects.
• Identify opportunities for process improvements and drive initiatives to enhance the efficiency and effectiveness of data operations.
• Has strong conceptual understanding of Data Warehousing and ETL, Data Governance and Security, Cloud Computing, and Batch & Real Time data processing
• Ability to build/drive reusable frameworks that can drive efficiency of the overall data system
• Has executed and lead multiple projects including on - streaming, batch, large data pipelines, etc.
• Manages conversation with the client stakeholders to understand the requirement and translate it into technical outcomes.

Required Tech Stack:

• Has strong execution knowledge of Data Modeling, Databases in general (SQL and NoSQL), software development lifecycle and practices, unit testing, functional programming, etc.
• Working knowledge of an ETL and/or orchestration tools like IICS, Metallion, Airflow, Azure Data Factory, AWS Glue, GCP Composer, etc.
• Working knowledge of one or more Data Warehouse like Snowflake, Redshift, Hive, Big Query, etc.
• Proficient in Spark and can optimize Spark jobs with ease.
• Proficient in at least one programming language used in data engineering, such as Python (Non-negotiable) and Scala/Rust/Java
• Understanding of Medallion architecture pattern
• Has strong SQL knowledge along with optimization skills

Required Non-Tech Stack

• Strong problem-solving skills with an ability to assess the financial impact of decisions, both in running the delivery team and delivering solutions to clients.
• Proficient in written and verbal communication and able to hold conversations with mid-management-level clients.
• Ability to recognize pragmatic alternatives vis-à-vis a perfect solution and get the delivery teams on board to pursue them, balancing time priorities with potential business impact.
• Strong people skills, including conflict resolution, empathy, communication, listening, and negotiation.
• Shows proficiency in providing technical guidance and provide leadership and mentorship to the delivery team.
• Self-driven with a strong sense of ownership.

Preferred Educational Qualifications

• B.E/B.Tech, MCA, M.Sc. (Mathematics, Statistics)