Engineering Manager

As an Engineering Manager, you will lead a high-performing team of data engineers focused on building robust, scalable, and secure data platforms. You will be responsible for driving the successful execution of data engineering projects, mentoring team members, and collaborating with cross-functional stakeholders to ensure alignment with business goals and technical standards. This role combines technical leadership with strategic planning to deliver efficient data solutions that support advanced analytics and machine learning initiatives. Key Responsibilities Lead a team of data engineers in designing, building, and maintaining scalable data pipelines and infrastructure. Collaborate with cross-functional teams to ensure client data systems meet high standards of quality and performance. Mentor and develop team members, fostering a collaborative and inclusive environment. Conduct performance reviews, set goals, provide feedback, and identify professional development opportunities. Plan, execute, and deliver data engineering projects on time and within scope. Work with stakeholders to gather requirements, define priorities, and set project timelines. Align projects with overall business objectives and data strategy. Oversee the design and maintenance of data pipelines, ETL processes, and data warehouses. Ensure data quality, integrity, and security across all data engineering initiatives. Drive process improvements to enhance efficiency and effectiveness of data operations. Apply expertise in data warehousing, data governance and security, cloud computing, and both batch and real-time data processing. Build reusable frameworks to enhance the efficiency of the data system. Lead multiple projects including streaming, batch processing, and large-scale data pipelines. Engage with client stakeholders to understand requirements and translate them into technical outcomes. Required Skills and Experience Required Technical Skills: Strong hands-on experience with data modeling, SQL and NoSQL databases, the software development lifecycle, best practices, unit testing, and functional programming Proficient in at least one data engineering programming language (Python mandatory; Scala, Rust, or Java preferred) Experience with ETL and orchestration tools such as IICS, Metallion, Airflow, Azure Data Factory, AWS Glue, or GCP Composer Experience with data warehousing tools including Snowflake, Redshift, Hive, or BigQuery Proficient in Spark with the ability to optimize Spark jobs Strong understanding of Medallion architecture Advanced SQL skills with experience in query performance optimization Required Non-Technical Skills: Strong problem-solving ability with awareness of the financial impact of technical decisions Excellent written and verbal communication; able to engage with mid-management clients Pragmatic decision-making mindset; capable of balancing timelines with business impact Strong interpersonal skills: conflict resolution, empathy, listening, and negotiation Proven leadership and mentoring capabilities High sense of ownership and self-drive Good to Have: Experience with machine learning and advanced analytics technologies Familiarity with data visualization tools and techniques Knowledge of data governance, privacy, and compliance frameworks Experience with containerization/orchestration (Docker, Kubernetes) Exposure to graph databases, data virtualization, and federation techniques Proficiency in data profiling and quality management

Location: bangalore, IN

Posted Date: 6/17/2025