We are looking for a Senior Data Engineer to design, build, and optimize scalable data platforms and pipelines. You will work closely with analytics, data science, and business teams to deliver reliable, high-quality data using modern cloud technologies. Hands-on expertise in Databricks and Snowflake is essential.

Key Responsibilities

- Design, develop, and maintain scalable batch and real-time data pipelines using Databricks (PySpark/Spark SQL) and Snowflake.
- Build and optimize ELT/ETL workflows to ingest data from diverse sources (databases, APIs, files, streaming platforms).
- Implement data lakehouse and data warehouse solutions following medallion architecture (Bronze/Silver/Gold).
- Optimize performance and cost across Databricks clusters and Snowflake warehouses.
- Develop and manage data models (dimensional, star/snowflake schemas) to support analytics and reporting.
- Implement data quality, validation, lineage, and governance frameworks.
- Set up CI/CD pipelines and infrastructure-as-code for data workflows.
- Orchestrate pipelines using tools such as Airflow, Azure Data Factory, or Databricks Workflows.
- Ensure data security, access controls, and compliance with organizational standards.
- Collaborate with data scientists, analysts, and product teams to translate requirements into technical solutions.




- Troubleshoot production issues and ensure pipeline reliability and SLA adherence.

Required 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.
- Strong hands-on experience with Databricks (Spark, Delta Lake, Unity Catalog, Workflows, notebooks).
- Solid hands-on experience with Snowflake (Snowpipe, Streams & Tasks, Time Travel, virtual warehouses, RBAC, performance tuning).
- Advanced proficiency in SQL and Python (PySpark).
- Solid understanding of data warehousing, data modeling, and ETL/ELT concepts.
- Experience with at least one major cloud platform (AWS, Azure, or GCP).
- Experience with version control (Git) and CI/CD practices.
- Strong problem-solving, communication, and stakeholder management skills.

Preferred Qualifications

- Databricks or Snowflake certifications (e.g., Databricks Certified Data Engineer, SnowPro Core/Advanced).
- Experience with streaming technologies (Kafka, Event Hubs, Kinesis, Structured Streaming).
- Familiarity with Airflow, or similar transformation/orchestration tools.
- Exposure to ML/MLOps pipelines and feature engineering.
- Experience working in Agile/Scrum environments.

📌 Data Engineer (Databricks & Snowflake) (Bengaluru)
🏢 CONSIGN SPACE SOLUTIONS PRIVATE
📍 Bengaluru