Senior Data Engineer (Python/Spark)
ASCENDING
Job Description
Our client is a leading provider of financial and economic data to the investment banking industry. They are seeking an experienced Senior Data Engineer to join and growing team.
- This role is only available for W2 or individual contracts. Please no C2C.
- Hybrid, 1~2 days required onsite in Mclean, VA
Responsibilities:
- Analyze system requirements and design responsive algorithms and solutions.
- Build efficient ETL pipeline using Spark.
- Use big data and cloud technologies to produce production quality code.
- Engage in performance tuning and scalability engineering.
- Work with team, peers and management to identify objectives and set priorities.
- Perform related SDLC engineering activities like sprint planning and estimation.
- Work effectively in small agile teams.
- Provide creative solutions to problems.
- Identify opportunities for improvement and execute.
Requirements:
- 4+ years of proven professional experience working in the IT industry.
- AWS EMR experience.
- Degree in Computer Science or related domains.
- Candidate must have 3-5 years of demonstrated experience in building big data solutions on AWS cloud primarily with PySpark, preferably in Data Analytics space.
- Minimum 3 - 5 years experience in application development using Python.
- Minimum 3 - 5 years of experience working with Spark
- Must have hands on experience developing data engineering solutions in Python using: S3, EMR, Glue, Athena, Kafka and notebooks.
- Must have hands on development experience in building distributed Big Data solutions including ingestion, caching, processing, consumption, logging & monitoring.
- Position requires strong technical communication skills.
Bonus:
- Big Data and Open Source technical experience.
- Agile (Scrum) methodology.
- Experience developing SaaS application backends and APIs using a variety of tools.
- Experience turning abstract business requirements into concrete technical plans.
- Proficiency with algorithms (including time and space complexity analysis), data structures, and software architecture.
- Must be a quick learner to evaluate and embrace new technologies in the Big data space.
Thanks for applying!
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