Big Data Engineer

#HiringBig Data Engineer Title: Big Data Engineer Location: Rockville, MD or McLean, VA (Hybrid – 3 days onsite with 2 days remote) (Need Local Candidate) Duration: 6 Months with possible extension Interview process: Prescreen, Phone, Onsite panel Must haves: spark, hadoop, scala, hive scripting is a must- python or perl must be expert level in Complex SQL- window functioning, complex multiple joins, cloud experience is mandatory-S3, glue, emr, athena AI- How to use AI for prompt engineering Github Copiliot Chatgpt Q Responsibilities Design, develop, and maintain scalable data pipelines using technologies such as Spark, Hadoop, Python, and Scala. Build and optimize data ingestion, transformation, and storage solutions for large-scale datasets. Optimize existing data pipelines for performance, scalability, and reliability. Collaborate with cross-functional teams to translate business requirements into technical solutions. Monitor, troubleshoot, and resolve data pipeline issues in production environments. Implement automated testing and data quality checks across pipelines. Stay current with emerging big data and cloud technologies to continuously improve the platform. Support data scientists and analysts by enabling reliable access to high-quality data. Qualifications Bachelor's degree in Computer Science or a related field, or equivalent experience. 5 years of experience building enterprise-scale data solutions. Strong experience with big data technologies such as Spark, Hadoop, Hive, and Trino. Proficiency in Python or Scala, with solid object-oriented and/or functional programming skills. Strong SQL skills, including complex queries, joins, and window functions. Experience working with large datasets and troubleshooting performance, scalability, and data quality issues. Experience with cloud platforms, preferably AWS (e.g., S3, EMR, Glue, Athena, Lambda). Familiarity with Agile development practices and CI/CD pipelines. Strong communication skills and ability to work effectively in a fast-paced environment. Preferred Qualifications Experience managing production ETL or data pipeline systems. Exposure to AI-assisted development tools (e.g., Copilot, ChatGPT, Q Developer). Experience with Spark performance tuning and optimization. AWS certifications or equivalent cloud experience. Drop resume : [Upgrade to PRO to see contact]