AWS Data Engineers
Big Data, AWS, Redshift, Snowflake, SQL, Python, PySpark
Description
GSPANN is looking for Data Engineers with expertise in Amazon Web Services (AWS). Our culture fosters individual initiative and excellence. Join our global workforce to unleash a pool of opportunities.
Who We Are
GSPANN has been in business for over a decade, with over 2000 employees worldwide, and servicing some of the largest retail, high technology, and manufacturing clients in North America. We provide an environment that enables career growth while still interacting with company leadership.
Visit Why GSPANN for more information.
Location: Gurugram / Hyderabad / Pune
Role Type: Full Time
Published On: 28 October 2024
Experience: 6+ Years
Description
GSPANN is looking for Data Engineers with expertise in Amazon Web Services (AWS). Our culture fosters individual initiative and excellence. Join our global workforce to unleash a pool of opportunities.
Role and Responsibilities
- Design, develop and maintain a data platform that is accurate, secure, available, and fast.
- Integrate and maintain a variety of data sources: multiple databases, APIs, SAASs, files, logs, events, etc.
- Create standardized datasets to service a wide variety of use cases.
- Develop subject-matter expertise in tables, systems, and processes.
- Partner with product and engineering to ensure product changes integrate well with the data platform.
- Partner with diverse stakeholder teams, understand their challenges and empower them with data solutions to meet their goals.
- Perform data quality on data sources and automate and maintain a quality control capability.
Skills and Experience
- 5+ years of experience as a Data Engineer.
- Hands-on with Star/Snowflake schema design, data modeling, data pipelining and MLOps.
- Experience in Data Warehouse technologies (e.g. Snowflake, AWS Redshift, etc.)
- Expertise in AWS data pipelines (Lambda, AWS glue, Step functions, etc)
- Fintech or Financial services industry experience is an advantage.
- Proficiency in SQL and at least one major programming language like Python, Java is desirable.
- Experience with Data Analysis Tools such as Looker or Tableau.
- Good understanding of Pandas, Numpy, Scikit-learn, and Jupyter notebooks preferred, familiarity with Git, GitHub, and Jira.
- A keen eye for detail. You catch and resolve data quality issues before others do.
- Always looking for opportunities to simplify, automate tasks, and build reusable components. Use good judgment in applying new technologies to solve business problems.
- End-to-end data platform support experience.
- Build strong relationships with analysts, business, and engineering stakeholders.
- Prioritize work well and break down ambiguous problems into actionable tasks and execute them.
- Familiarity with agile methodologies will go a long way.
- Experience in the fintech industry.
- Aware of or eagerness to learn, about the Private Equity/Venture Capital ecosystem and associated secondary market.
