Data Engineering Manager (Gurugram/Noida)

Job Description

Job Title: Data Engineering ManagerLocation: Noida/Gurugram | Employment Type: Full-TimeExperience: 12+ years in data engineering, 5+ years in technical leadership About Us[Company Name] is a data-driven pioneer committed to transforming raw data into actionable insights that fuel innovation and business success. We leverage modern cloud technologies and scalable architectures to build next-generation data platforms. Join us to lead a team of elite engineers and shape the future of enterprise data ecosystems. Role OverviewAs a Data Engineering Manager, you will spearhead the design, execution, and optimization of mission-critical data infrastructure. You will lead a team of senior data engineers to deliver high-performance solutions using Databricks, Azure, Apache Spark, Kafka, Airflow, and Snowflake. This role demands a strategic leader who can balance technical excellence with cross-functional collaboration to drive scalable, secure, and cost-effective data solutions. Key ResponsibilitiesStrategic Leadership:Mentor and manage a team of senior data engineers, fostering innovation, accountability, and agile practices.Define long-term data architecture roadmaps aligned with business objectives.Advanced Data Platform Development:Architect and optimize enterprise-grade data pipelines using Databricks and Apache Spark for batch/stream processing.Design event-driven systems with Kafka and orchestrate workflows via Airflow for end-to-end data lifecycle management.Cloud & Modern Data Stack:Lead cloud-native deployments on Azure (e.g., Synapse, Data Factory) and integrate with Snowflake for analytics-ready data warehousing.Implement governance frameworks for data quality, security, and compliance (GDPR, CCPA).Scalability & Innovation:Optimize resource allocation (cost, performance) for big data workloads in distributed environments.Evaluate emerging tools (e.g., Delta Lake, dbt) to enhance platform capabilities and reduce technical debt.Stakeholder Collaboration:Partner with C-suite, data scientists, and product teams to align engineering efforts with business KPIs.Translate complex business requirements into scalable technical solutions. QualificationsMust-Have:12+ years in data engineering, including 5+ years managing high-performing teams.Expert-level proficiency:Databricks (Delta Lake, Spark SQL, Unity Catalog).Azure (Data Lake, Synapse, DevOps).Apache Spark (structured streaming, performance tuning).Kafka (event sourcing, stream processing).Airflow (DAG optimization, custom operators).Snowflake (data sharing, clustering, RBAC).Mastery of Python/Scala, SQL, and IaC tools (Terraform, ARM templates).Proven success in scaling petabyte-scale data platforms. Nice-to-Have:Certifications: Databricks Certified Architect, Azure Solutions Architect, Snowflake SnowPro.Experience with MLOps or real-time analytics (e.g., Kafka Streams, Flink).Contributions to open-source projects or thought leadership (blogs, conferences). What We OfferCompetitive salary + equity/stocks + performance bonuses.Flexible hybrid/remote work model.Sponsorship for advanced certifications and conferences.A seat at the table for strategic decision-making.