Senior Data Engineer

We are seeking a Senior Data Engineer to join our team.
This role involves a blend of engineering and analytical responsibilities. You will develop and maintain data infrastructure while also analyzing cost data, identifying trends, and working closely with teams to optimize cloud spend. With a heavy focus on AWS, this position requires a strong understanding of AWS services and cost structures. You will leverage tools like Python, Databricks, Snowflake, Airflow, and Looker to deliver impactful insights and solutions that drive cost optimizations and decision-making.

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Responsibilities

• Design, build, and maintain scalable ETL pipelines to process and transform large volumes of cloud cost and usage data
• Integrate data from multiple sources, including AWS, into centralized data lakes or warehouses like Snowflake
• Develop and maintain data models to support cost analysis and reporting needs
• Optimize query performance and storage efficiency for large-scale datasets
• Automate recurring data processing tasks and implement robust monitoring for data pipelines
• Ensure data accuracy and reliability through validation processes
• Analyze cloud cost data to identify trends, anomalies, and optimization opportunities
• Work closely with teams to investigate spending changes and resolve cost anomalies
• Collaborate with stakeholders to understand cost drivers and provide actionable insights
• Support teams in building dashboards and visualizations to track key cost metrics
• Create reports and presentations to communicate findings and recommendations to leadership
• Partner with teams to develop strategies for cost reduction and operational efficiency

• Bachelor's degree in Computer Science, Data Engineering, Data Analytics, or a related field
• 3+ years of experience in a data engineering, data analysis, or hybrid role
• Knowledge of AWS services (e.g., EC2, S3, RDS, Lambda) and their cost structures
• Proficiency in SQL and experience with relational databases like Snowflake or Redshift
• Familiarity with Databricks and Spark for large-scale data processing
• Hands-on experience with ETL tools and frameworks (e.g., Databricks, Apache Airflow)
• Programming experience in Python for data analysis and pipeline development
• Experience with BI tools like Looker or Tableau for creating dashboards and visualizations
• Excellent problem-solving skills and the ability to interpret and analyze large datasets

• Experience with Kubernetes, Docker, or containerization technologies
• Understanding of cloud cost management tools and strategies
• Strong communication skills for presenting insights to stakeholders and leadership

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• Employee financial programs
• Paid time off and sick leave
• Upskilling, reskilling and certification courses
• Unlimited access to the LinkedIn Learning library and 22,000+ courses
• Global career opportunities
• Volunteer and community involvement opportunities
• EPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn