OVERVIEW

We are seeking a highly skilled and proactive Senior Data Engineer to design, build, and optimize data pipelines and cloud-based data solutions. The ideal candidate will have hands-on expertise with Snowflake, AWS (API Gateway, Lambda, IAM, S3, SNS, SQS), DBT, Terraform, and Power BI, with strong experience in SQL and Python for data engineering tasks.

REQUIREMENTS

• Bachelor’s Degree in Computer Science, Information Systems, or related field.
• 5+ years of hands-on technical experience in data engineering or software engineering.
• 3+ years building/supporting SQL-based data pipelines (Snowflake, MSSQL, or similar).
• 3+ years of cloud experience (minimum 1+ years with AWS).
• 2+ years of experience with Power BI (DAX, data modeling, report optimization).
• 2+ years of programming experience with Python for data engineering tasks.
• Experience with CI/CD tools (CDK, Terraform, GitHub Actions, or similar).
• Knowledge of data governance frameworks is a plus.
• Experience with DBT, Terraform, and Octopus is an added advantage.

PREFERRED SKILLS

• Strong problem-solving and analytical skills.
• Excellent communication skills to interact with technical and non-technical stakeholders.
• Experience working in capital markets or similar industries is a plus.
  Job Type: Full-time
  Pay: $50.00-$53.00 per hour

Education:

• Master’s Degree (required)

Experience:

• Snowflake: 6 years (required)
• Data Engineer: 10 years (required)
• AWS services such as Lambda, Redshift, DMS: 8 years (required)
• Power BI: 6 years (required)

• Design, develop, and maintain scalable ETL/data pipelines using AWS services (Lambda, API Gateway, S3, etc.).
• Manage and optimize Snowflake tables, DDL/DML queries, and DBT models.
• Write, modify, and optimize complex SQL queries for data ingestion, transformation, and reporting.
• Integrate data from multiple sources (on-premise and SaaS applications) into cloud data warehouses.
• Develop and enhance data visualizations and dashboards in Power BI, including DAX and performance tuning.
• Implement CI/CD practices using Terraform, GitHub Actions, or similar tools.
• Utilize Python for data processing, large dataset manipulations, and API-based ingestion.
• Ensure data governance, security, and compliance standards are maintained.
• Collaborate with cross-functional teams to support data-driven initiatives.
• Continuously learn and adapt to emerging tools and technologies.