Lead Data Engineer Remote
Lead Data Engineer Description
We are seeking a Lead Data Engineer to join our team.
This position combines engineering and analytical duties. You will develop and maintain data infrastructure while analyzing cost data, identifying trends, and collaborating with teams to optimize cloud expenses. Primarily focusing on AWS, this role demands a solid understanding of AWS services and cost structures. You will utilize tools such as Python, Databricks, Snowflake, Airflow, and Looker to provide impactful insights and solutions that enhance cost optimizations and support decision-making.
EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.
#LI-DNI
Responsibilities
- Design, construct, and sustain scalable ETL pipelines to process and adjust large volumes of cloud cost and usage data
- Merge data from various sources, including AWS, into centralized data repositories like Snowflake
- Create and uphold data models to aid cost analysis and reporting requirements
- Enhance query output and storage effectiveness for vast datasets
- Automate repetitive data processing jobs and set up robust monitoring for data pipelines
- Guarantee data precision and dependability via validation techniques
- Examine cloud cost data to pinpoint trends, anomalies, and opportunities for optimization
- Engage intimately with teams to review expenditure changes and address cost anomalies
- Cooperate with stakeholders to comprehend cost determinants and offer actionable insights
- Assist teams in crafting dashboards and visualizations to monitor critical cost indicators
- Compile reports and presentations to convey findings and suggestions to leadership
- Collaborate with teams to formulate strategies for cost reduction and operational enhancement
Requirements
- Bachelor’s degree in Computer Science, Data Engineering, Data Analytics, or a related field
- 5+ years of experience in data engineering, data analysis, or a combined role
- 1+ years of relevant leadership experience
- Expertise in AWS services (e.g., EC2, S3, RDS, Lambda) and their cost frameworks
- Proficiency in SQL and skills in 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 creation
- Experience with BI tools like Looker or Tableau for constructing dashboards and visualizations
- Excellent problem-solving abilities and the capability to interpret and analyze vast datasets
Nice to have
- Background in Kubernetes, Docker, or containerization technology
- Understanding of cloud cost management tools and techniques
- Strong communication capabilities for presenting insights to stakeholders and leadership
We offer
- Connectivity Bonus (15,000 ARS are paid with a salary receipt at the end of each month as a non-wages concept)
- Medicina Prepaga (It covers the collaborator and direct family group)
- Paternity Leave (Two additional days are added to what is established by law, total of 4 days)
- Discounts card
- English Training (English lessons, twice per week)
- Training Program (Access to multiple customized training plans according to the needs of each role within the company)
- Marriage bonus (The company doubles the allowance established by law that ANSES offers)
- Referral Program (Referral bonus is paid when the referral of a collaborator joins the Company)
- External Agreements and Discounts
- Vacations: 14 calendar days a year
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