Lead Data Engineer

Tudip Technologies · Remote

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Last observed by our collector: 9 October 2026 at 12:37 am IST. This is not a manual review or a confirmation from the employer.

Employer requisition: lead-data-engineer

Job type and experience labels are automated discovery categories. The employer determines eligibility. Retained employer experience wording: 7+ years.

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Retained employer experience wording: 7+ yearsAttendance and availability: I checked the employer page for work location, office attendance, start date and duration.Current requisition: I checked the current employer requisition and its application requirements.

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Collected role description

Lead Data Engineer We are looking for an experienced Lead Data Engineer to design, build, and manage scalable data pipelines and platforms. The ideal candidate will lead the data engineering team, collaborate with cross-functional stakeholders, and ensure high-quality, reliable, and secure data solutions that support business and analytics needs. Hands-on experience with Databricks is mandatory for this role. Key Responsibilities Lead the design, development, and maintenance of robust and scalable data pipelines using Databricks. Architect end-to-end data solutions including data ingestion, transformation, storage, and analytics. Build and optimize data workflows using Databricks, Spark, and cloud data platforms. Guide and mentor a team of data engineers, ensuring best practices and code quality. Collaborate with product managers, data scientists, analysts, and business teams to understand data requirements. Ensure data quality, governance, security, and compliance standards are met. Optimize performance and cost of data pipelines and platforms. Review technical designs, code, and deployments. Troubleshoot and resolve complex data-related issues. Participate in strategic planning and roadmap discussions for data platforms. Required Skills & Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. 7+ years of experience in data engineering or related roles. Mandatory hands-on experience with Databricks (Delta Lake, Databricks SQL, notebooks, jobs, workflows). Strong experience with Apache Spark and distributed data processing. Proficiency in SQL and programming languages such as Python, Scala, or Java. Experience with cloud platforms (AWS, Azure, or GCP). Expertise in data warehousing solutions (Snowflake, Redshift, Big Query, etc.). Experience with ETL/ELT tools and orchestration frameworks (Airflow, dbt, etc.). Strong understanding of CI/CD, version control, and Dev Ops practices. Excellent leadership, communication, and problem-solving skills. Preferred Skills Experience leading or mentoring data engineering teams. Knowledge of real-time data processing and streaming (Kafka, Spark Streaming, etc.). Exposure to BI and analytics tools. Experience working in Agile/Scrum environments.

Collected experience requirement

7+ years