Job ResponsibilitiesResponsible for leading a team of talented data engineers responsible for designing, building, and maintaining scalable data pipelines and infrastructureWork closely with cross-functional teams to ensure client data systems meet the highest standards of quality and performanceLead, mentor, and develop a team of data engineers, fostering a collaborative and inclusive team environmentConduct regular performance reviews, provide feedback, and set goals for team membersIdentify and address skill gaps, and provide opportunities for professional developmentPlan, execute, and deliver data engineering projects on time and within scopeCoordinate with stakeholders to gather requirements, set priorities, and define project timelines.Ensure projects align with overall business objectives and data strategyOversee the design, development, and maintenance of data pipelines, ETL processes, and data warehouseEnsure 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 processingAbility to build/drive reusable frameworks that can drive efficiency of the overall data systemHas 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 StackStrong experience with Databricks, Spark, and cloud platforms (Azure, AWS,



GCP).Architect and deploy cloud-based data solutions (Azure, AWS, GCP).Define CI/CD strategies for data pipelines using Terraform, Azure DevOps, or GitHub Actions.Implement data cataloging, lineage tracking, and access control (Unity Catalog,Collibra, Alation).Ensure compliance with GDPR, CCPA, and industry-specific data security policies.Develop strategies for distributed computing, parallel processing, and caching mechanisms.Required Non-Tech StackPartner with data architects, product managers, and business leaders to define data requirements and align engineering efforts with business objectives.Define data engineering standards and playbooks to streamline development.Oversee end-to-end project execution, from scoping to delivery.Stay updated with emerging trends in data engineering, AI, and analytics to continuously improve architectures.Evaluate and recommend new data tools, frameworks, and best practices.Ability to translate complex technical concepts into business-friendly language.Excellent communication, leadership, and stakeholder management.Positive to Have Tech StackExperience with machine learning and advanced analytics technologiesFamiliarity with data visualization tools and techniquesKnowledge of data security and privacy practicesUnderstanding of data governance and compliance frameworksExperience with containerization and orchestration technologies (e.g., Docker, Kubernetes)Experience with graph databases and graph processing frameworksExperience with data virtualization and data federation techniquesProficiency in data profiling and data quality managementPreferred Educational QualificationsB.E/B.Tech, MCA, M.Sc. (Mathematics, Statistics)

📌 Lead Data Engineer (Vasanth Nagar)
🏢 MathCo
📍 Vasanth Nagar