Manager/Senior Manager

Manager/Senior Manager - Data Engineering (8-12 Years)Cognitio Analytics | Gurgaon (Hybrid)Location: Gurgaon (Hybrid)Experience: 8–12 yearsWebsite: Type: Full-TimeAbout Cognitio Analytics:Founded in 2013, Cognitio Analytics is a leading provider of AI/ML-driven productivity solutions for large enterprises. We have been recognized for our award-winning Smart Operations and Total Rewards Analytics solutions, built on deep R&D and a commitment to innovation.Our solutions help clients transform complex operations such as claims processing and commercial underwriting, and maximize ROI on Total Rewards programs through our proprietary Total Rewards Data Factory .Cognitio Analytics is proudly certified as a Great Place to Work , reflecting our focus on creating an innovative, collaborative, and employee-centric environment.Role: Manager/Senior Manager - Data EngineeringWe are seeking an experienced Data Engineering Lead (8–12 years) to drive the design, development, and optimization of our cloud-based data platforms. This role involves leading a team of data engineers, managing end-to-end project execution, and collaborating closely with cross-functional stakeholders.Key Responsibilities:Lead the design, build, testing, and deployment of scalable data pipelines and models on the production data platform.Define and implement processes for operational excellence across agile development and data engineering workflows.Oversee data infrastructure including data warehouses, data lakes, and integration components for efficient ETL/ELT.Collaborate with clients, vendors, leadership, and internal teams for smooth delivery and ongoing support.Contribute to roadmap planning and prioritization with business owners.Ensure adherence to best practices in data modeling, data quality, governance, reusability, and security.Evaluate and adopt modern tools, technologies, and frameworks to enhance team efficiency.Lead project planning, execution, tracking, and quality control for data engineering initiatives.Establish and track KPIs to measure team performance and solution effectiveness.Stay updated with advancements in Azure Cloud and data engineering technologies.Qualifications:8–12 years of experience in Data Engineering, analytics, data warehousing, and data management.Experience managing data engineers through planning, execution, monitoring, and delivery cycles.Strong knowledge of cloud-based data tools and platforms, especially Azure.Experience building scalable systems supporting data transformation, metadata, security, governance, and workload management.Expertise in designing and optimizing models for RDBMS, NoSQL, and data warehouse environments.Proven ability to lead complex data engineering initiatives and drive innovation.Excellent communication, stakeholder management, and leadership skills.Must Have Skills:SQL, Python, PySpark, Spark SQL, Spark, Distributed SystemsDatabricks, ADLS Gen2, Azure DevOps, Azure Data FactoryETL/ELT pipelines, Data Warehousing, Datamarts, Data Modeling, Data GovernanceAgile practices, SDLC, DevOps, CI/CD for data workflowsDeep understanding of Microsoft Azure (preferred)Hands-on Azure Databricks (ingestion, transformation, workflow orchestration, job optimization)Experience with ADLS Gen2 setup and best-practice data lake architecturesFamiliarity with big data frameworks (e.g., Apache Spark)Knowledge of Azure Key Vault for secure secret and certificate managementGood to Have:Event HubsWorkflow orchestration toolsCosmos DBPower BIProfessional Services backgroundScala or JavaGurgaon (Hybrid) — Candidates must be comfortable working in a hybrid model from our Gurgaon office.Cognitio Analytics is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, sex, national origin, age, religion, marital status, sexual orientation, gender identity, gender expression, veteran status, disability, or any other protected category. All employees must adhere to Cognitio’s Security and Privacy policies to ensure protection of company and client data. Our compensation ranges are designed to be market competitive and form part of a total rewards package that includes bonuses, equity options, benefits, and additional opportunities. Individual compensation is determined by experience, skills, and role fit.