Senior Data Engineer

Overview

Senior Data Engineer at Mindera to design, develop, maintain and optimise data pipelines and analytical data models, with strong hands-on work across Snowflake, dbt, SQL, Python and AWS data services.

What you'll do

• Design, develop and maintain scalable data pipelines and transformation workflows.
• Build and optimise data models using Snowflake to support analytics and reporting requirements.
• Manage Snowflake virtual warehouses, optimise queries, and improve performance and compute efficiency.
• Develop and maintain dbt models using dbt Core and dbt Cloud, including incremental models, macros, and automated testing.
• Write complex, efficient SQL queries for data transformation, validation, and processing.
• Develop Python scripts for data engineering, pipeline automation, and workflow management.
• Work with Snowflake stored procedures and Python-based data processing solutions.
• Build, maintain, and troubleshoot Apache Airflow DAGs for data pipeline orchestration.
• Implement and support data ingestion and processing workflows using AWS services, including S3, Glue, and Kinesis Data Firehose.
• Design and implement dimensional data models, including fact tables, dimension tables, and star/snowflake schemas.
• Monitor data pipelines, troubleshoot production issues, and ensure data quality, consistency, and reliability.
• Collaborate with analytics engineers, data engineers, analysts, and other stakeholders to translate business requirements into effective data solutions.
• Follow best practices for version control, testing, documentation, deployment, and maintainability.
• Take ownership of existing data workflows and contribute to continuous improvements in pipeline performance and data modelling.

What you'll need

• 8–12 years of overall experience in Data Engineering or related data disciplines.
• Strong hands-on experience with Snowflake data warehousing, including warehouse management, query optimisation, and performance tuning.
• Knowledge of Snowflake architecture, compute management, and data modelling.
• Strong experience developing and maintaining dbt projects, with hands-on expertise in incremental models, macros, and dbt testing.
• Understanding of dbt model dependencies, documentation, and deployment workflows.
• Advanced SQL skills, including complex joins, CTEs, window functions, and aggregations.
• Experience optimising queries and processing large datasets.
• Experience developing Python scripts for data engineering and pipeline automation.
• Experience building or maintaining Airflow DAGs.
• Hands-on experience with AWS data services, including Amazon S3, AWS Glue, and Amazon Kinesis Data Firehose.
• Ability to troubleshoot and maintain production data pipelines.
• Strong understanding of dimensional modelling principles, including designing fact and dimension tables and star and snowflake schemas.
• Proven experience working with Snowflake, dbt, SQL, Python, and AWS data services.
• Experience maintaining and enhancing production-grade data pipelines and analytical models.
• Ability to work independently, solve complex technical problems, and take ownership of existing data solutions.
• Strong communication and collaboration skills.

Nice to have

• Previous hands-on experience in an Analytics Engineering role.
• Familiarity with Snowflake stored procedures and Python-based integrations.
• Experience using Apache Airflow for pipeline orchestration, scheduling, and monitoring.

Details

• Locations: Chennai, Tamil Nadu, India; Bengaluru, Karnataka, India.
• Flexible working hours (self-managed).
• Annual bonus, subject to company performance.
• Access to Udemy online training.