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VdartInc
Alpharetta, GA
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Job Description :
Senior DATA Engineer Location: Remote initially, then in Chicago IL IMPORTANT NOTE: For the Requirement below, we need strong candidates who have hands-on development experience and very strong and recent experience on Spark/Pyscala. Please carefully review the profiles you are presenting and do not just forward profiles with no actual working experience. DATA ENGINEER 6+ years of experience | Candidate should possess at least 6 plus years of Development & Production support experience Skill Set required 5+ years of experience (Sr-level) Strong Programming experience with object-oriented/object function scripting languages: mandatory experience in Scala/PySpark 5+ years of experience (Mid-level) Experience with big data tools: Hadoop, Apache Spark etc 1+ years of strong technical Experience with AWS cloud services and DevOps engineering: S3, IAM, EC2, EMR, RDS, Redshift, Cloudwatch with Docker, Kubernetes, GitHub, Jenkins, CICD Experience with stream-processing systems: Spark-Streaming, etc. (Nice to have) 1+ Years of experience with relational SQL, Snowflake and NoSQL databases, like Postgres and Cassandra. Good communication skills, sense of ownership and open to learn attitude. Roles & Responsibilities Create and maintain optimal data pipeline architecture, Assemble large, complex data sets that meet functional / non-functional business requirements. Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability etc. Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS 'Big data' technologies. Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.