Senior Data Engineer

We are looking for a skilled Senior Data Engineer to design, build, and optimize scalable, cloud-based data platforms. The ideal candidate brings strong experience with modern data warehouses such as Snowflake, Databricks, or Amazon Redshift, along with expertise in data migration, ETL/ELT pipelines, and distributed data processing.

This role also requires hands-on experience with data migration and replication tools (e.g., AWS DMS) to enable seamless movement of data across systems and support near real-time data integration use cases.

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows
  

• Develop and optimize data models for analytics and business intelligence

• Implement and manage data platforms using Snowflake / Databricks / Redshift
  

• Lead data migration and replication initiatives using tools like AWS DMS, including full-load and CDC pipelines

• Work with large-scale structured and unstructured datasets
  

• Ensure data quality, integrity, and governance across systems

• Monitor, troubleshoot, and optimize data pipeline performance and cost efficiency
  

• Collaborate with Data Science, Product, and Business teams to deliver data solutions

• Contribute to architecture decisions and best practices
  

• Mentor junior engineers and provide technical leadership (for Lead role)

  
  
  

• 5+ years of experience in Data Engineering / Data Platform roles

• Hands-on experience with Snowflake, Databricks, or Amazon Redshift
  

• Strong expertise in SQL and data modeling
  

• Experience building and orchestrating pipelines using Airflow, dbt, or similar tools
  

• Proficiency in Python / PySpark / Scala
  

• Hands-on experience with AWS DMS (or similar data migration tools) for:

• Database migration (on-prem to cloud or cross-cloud)

• Change Data Capture (CDC) and real-time/near real-time data replication

• Performance tuning, monitoring, and troubleshooting of replication tasks

• Experience with cloud platforms (AWS / Azure / GCP)
  

• Strong understanding of data warehousing concepts and distributed systems
  

  
  
  

• Experience with real-time data streaming (Kafka, Spark Streaming, etc.)

• Familiarity with AWS SCT (Schema Conversion Tool) or similar migration utilities

• Exposure to BI tools (Tableau, Power BI, Looker)

• Knowledge of DevOps practices and CI/CD for data pipelines

• Experience managing large-scale production data systems
  

Impact: Play a critical role in maintaining system uptime and delivering seamless userc experiences.

Culture: Thrive in a fast-paced, collaborative environment focused on operational excellence.

Growth: Opportunity to expand into SRE, DevOps, or platform engineering roles.

Benefits: Competitive compensation, flexible work options, and continuous learning opportunities.