Cloud Data Engineer / Senior Data Visualization Analyst

We are looking for a Cloud Data Engineer with strong hands-on experience in data pipelines, cloud-native services (AWS), and modern data platforms like Snowflake or Databricks. Alternatively, were open to Data Visualization Analysts with strong BI experience and exposure to data engineering or pipelines. You will collaborate with technology and business leads to build scalable data solutions, including data lakes, data marts, and virtualization layers using tools like Starburst. This is an exciting opportunity to work with modern cloud tech in a dynamic, enterprise-scale financial services environment.

Key Responsibilities:

• Design and develop data pipelines for structured/unstructured data in AWS.
• Build semantic layers and virtualization layers using Starburst or similar tools.
• Create intuitive dashboards and reports using Power BI/Tableau.
• Collaborate on ETL designs and support testing (SIT/UAT).
• Optimize Spark jobs and ETL performance.
• Implement data quality checks and validation frameworks.
• Translate business requirements into scalable technical solutions.
• Participate in design reviews and documentation.

Skills & Qualifications:

• Must-Have:

• 10+ years in Data Engineering or related roles.
• Hands-on with AWS Glue, Redshift, Athena, EMR, Lambda, S3, Kinesis.
• Proficient in HiveQL, Spark, Python, Scala.
• Experience with modern data platforms (Snowflake/Databricks).
• 3+ years in ETL tools (Informatica, SSIS) & recent experience in cloud-based ETL.
• Strong understanding of Data Warehousing, Data Lakes, and Data Mesh.

• Preferred:

• Exposure to Data Virtualization tools like Starburst or Denodo.
• Experience in financial services or banking domain.
• AWS Certification (Data specialty) is a plus.