Data Engineering Manager

Role Overview :

As a Data Engineering Manager based in Gurugram, you will spearhead the design, development, and scaling of robust data platforms that serve as the backbone for our enterprise-wide decision-making. You will lead a high-performing team of engineers, collaborating closely with product managers, data scientists, and cross-functional business stakeholders to translate complex business requirements into high-performance data pipelines. Your work will directly influence the efficiency of our data ecosystem, ensuring that massive datasets are transformed into actionable insights that drive competitive advantage and operational excellence for our global clients.

Key Responsibilities :

- Architect and oversee the end-to-end lifecycle of large-scale data platforms to ensure high availability, scalability, and data integrity for business intelligence initiatives.

- Mentor and provide technical leadership to a team of data engineers, fostering a culture of engineering excellence, code quality, and continuous professional growth.

- Partner with stakeholders to define data strategy and roadmap, ensuring that technical investments align with long-term business objectives and revenue goals.

- Optimize data processing workflows and infrastructure costs by implementing best-in-class cloud-native solutions and automation frameworks.

- Drive the adoption of modern data engineering practices, including CI/CD, automated testing, and robust monitoring, to minimize downtime and improve delivery velocity.

Required Skillset :

- Demonstrated expertise in building and managing complex Big Data ecosystems using PySpark and Apache Airflow to handle petabyte-scale data ingestion and transformation.

- Proven ability to design and deploy cloud-native data architectures on AWS or GCP, with a deep understanding of managed services, security protocols, and cost-optimization strategies.

- Strong interpersonal skills with the ability to communicate technical vision to non-technical stakeholders and influence decision-making at the leadership level.

- Exceptional leadership capabilities, including experience in managing, coaching, and retaining diverse engineering talent in a fast-paced, hybrid work environment.

- A solid academic foundation in Computer Science or a related quantitative field, complemented by 12 to 17 years of progressive experience in data engineering and team management.

- High degree of adaptability to navigate ambiguous requirements and lead organizational change within a dynamic, high-growth corporate setting.

(ref:hirist.tech)