Tech Lead - Data Engineer

We are seeking a highly motivated and experienced Analytics and Data Engineer to guide the data engineering team.

The ideal candidate will have a strong background in data engineering, capable of data-driven decision-making. This role will be crucial in designing, developing, and maintaining our data infrastructure to support our business intelligence and analytics needs.

Key Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, or a related technical field.
• 6+ years of experience in a data engineering or similar role.
• Lead a team of data engineers and analysts, providing guidance, mentorship, and technical direction.

• Design, build, and maintain scalable and robust data pipelines and data warehouses using tools like Airflow, Amazon GLUE, Spark, etc.
• Establish and enforce best practices for data quality, security, and governance, including data cataloging.
• Work closely with cross-functional teams, including product, engineering, and business stakeholders, to understand data requirements and deliver effective solutions using agile methodologies.
• Monitor and optimize database performance and data pipeline efficiency, focusing on query optimization and cost management.
• Research and implement new technologies and methodologies to enhance our data capabilities, such as providing near real time insights using stream processing.
• Plan, manage, and execute data-related projects, ensuring they are completed on time and within budget.

• Expertise with advanced SQL, query optimization, and schema design for both OLAP and OLTP databases.
• Proficiency in Python, including experience with data manipulation libraries (e.g., Pandas, PySpark) and API integrations.
• Proven Strong Hands-on experience with cloud-based data platforms such as Google BigQuery, AWS Redshift, or Snowflake and their associated data services (e.g., Google Cloud Dataflow, AWS Glue and other).
• Deep understanding of data warehousing concepts, ETL/ELT principles, dimensional modeling (e.g., Star/Snowflake schemas), and real-time data ingestion techniques.
• Experience with a variety of data technologies (e.g., Apache Spark, Kafka, Airflow, dbt, Fivetran).
• Hands on experience with big data related technologies and distributed computing.
• Familiarity in Statistics & Probability, Predictive Modeling/Analysis, and experimental design
• Skilled in Data Visualization to transform data into clear, impactful stories that drive business insight.
• Expertise in analytical tools like - Superset, Tableau, power BI is must. Ability to patch open source codes to enhance features.
• Strong fundamental understanding of data structures and algorithms, SDLC, SOLID principles, and design patterns.