Lead Data Engineer

1 day ago

Yelahanka, India Movate Full time

Job title: Lead Data Engineer Location: Bangalore Experience: 6+ Years Summary: We are seeking an experienced Data Lead to own and drive the design, development, and optimization of modern data platform using Snowflake & DBT. The candidate needs to have hands-on expertise with Snowflake, DBT, and PySpark, combined with strong data architecture, team leadership, and stakeholder management skills. Key Responsibilities: 1. Data Architecture & Strategy: Drive the design and implementation of the enterprise data platform, leveraging Snowflake as the core data infrastructure. 2. Pipeline Development: Architect and deliver robust ETL/ELT pipelines in Snowflake and DBT to integrate data from diverse source systems. Expert in Snowflake internals (warehouse sizing, RBAC, partitioning, query tuning). Well aware of DWH schema design and hands on exp on SCD-2 implementation. 3. Full Development Lifecycle: Participate in all phases of solution delivery, including development, testing, deployment, and optimization. 4. Quality Assurance: Perform code reviews, ensure adherence to engineering best practices, and continuously improve code quality and ETL performance. 5. Issue Resolution: Diagnose, troubleshoot, and resolve complex ETL/ELT issues with efficiency and precision. 6. Cross-Functional Collaboration: Work closely with product, engineering, analytics, and business teams to solve complex data challenges and align solutions with organizational goals. Required Skills: 1. At least 6 years of professional experience, including hands-on work as a Data Lead with strong expertise in Snowflake and dbt. 2. Bachelor’s degree in Computer Science, Software Engineering, or a related discipline. 3. Solid working knowledge of SQL, PySpark, and Python data libraries such as NumPy, SciPy, Pandas, Dask, and SQLAlchemy. 4. Strong proficiency in Snowflake data warehousing, including schema design and implementation. Hands on exp in SCD-2 implementation. 5. Good exp in Data quality frameworks such as Great Expectations, Deequ to address data quality issues. 6. Experience with the AWS/Azure cloud services ecosystem, supported by relevant cloud certifications. 7. Demonstrated ability to lead and mentor small engineering or data development teams. 8. Excellent problem-solving abilities, with strong communication and collaboration skills. 9. Working knowledge of agile methodologies, especially sprint-driven development processes. Desired Skills: 1. Experience with big data technologies (e.G., PySpark, Hadoop, Kafka). 2. Understanding of data science and machine learning concepts, tools, and workflows.

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