Lead Data Engineer
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Job Description Summary:Envestnet, Inc. (NYSE:ENV) is a leading independent provider of technology‐enabled investment and practice management solutions to financial advisors who are independent, as well as those who are associated with small or mid‐sized financial advisory firms and larger financial institutions. Envestnet's technology is focused on addressing financial advisors' front, middle, and back‐office needs. Envestnet is headquartered in Chicago.
Major Responsibilities: Responsible for helping clients turn data into knowledge to help them make better decision, faster. Work with clients and team members to analyze and help define requirements, mine and analyze data, integrate data from a variety of sources, and participate in the design and implementation of reports, algorithms, and other data processing and analysis techniques. Deliver high-quality data pipelines for producing analytics-ready datasets. Responsible for delivering end-to-end analytics projects including, data: ingest, transportation, silence and visualization. Design and deploy databases and data pipelines to support analytics projects. Clearly document datasets, solutions, findings, and recommendations to be shared internally and externally. Learn and apply toold and technologies proficiently including: SQL (standard and DB-specific), Python, R, Spark/Scala, Bash, Hadoop, Spark, AWS, and Data science studio, Alteryx, Jupyter, RStudio, Tableau, and PowerBI. Build compelling visualizations and dashboards that address the analytic needs of the end-user or customer. Complete performance optimization for queries and dashboards, and develop and deliver clear, compelling briefings to internal and external stakeholders on his findings, recommendations and solutions. Analyze client data and systems to determine whether requirements can be met. Test and validate data pipelines transformations, datasets, reports and dashboards built by the team. Develop and communicate solutions architectures and present solutions to both business and technical stakeholders. Provide end user support to other data engineers and analysts.
Job Requirements: Applicant must possess a Bachelor’s or foreign equivalent degree in a Computer Science, Computer Engineering, MIS, Data Engineering or a related field and 6 years of professional experience in software programming, software development, data engineering or related role. Additionally, the applicant must have professional experience in the following: (1) 1+ years of experience in DataIku as a platform to develop pipelines; (2) 3+ years of experience in designing and deployment of research use cases using PySpark, Hive; (3) 3+ years of experience in developing Spark code using Spark-SQL/Streaming for faster processing of data; (4) 3+ years of experience with AWS for running clusters using EMR and EC2 and maintain the jobs, storing data on S3; (5) 2+ years of experience in Dockers to deploy the package on AWS and bring up the Cloud Formation Stack and EMR clusters; (6) 1 year of experience in Kafka for Streaming layer with downstream components; (7) 5+ years of experience in developing modules using Java 8; (8) 4+ years of experience in JIRA extensively to manage stories; (9) 4+ years of experience in Spark API over Java to perform analytics on data; (10) 1+ years of experience in Cucumber for merging specification and tests as one cohesive whole; (11) 1+ years of experience in SAT, PAT, PPT for the products; (12) 3+ years of experience in Continuous Integration and Continuous Delivery with Jenkins, GO-CD including Maven and Artifactory; (13) 2+ years of experience in Scala programming for Spark applications; (14) 4+ Experience with RDMS technologies like Oracle, DB2 and MySQL; and (15) 1+ Experience with SPLUNK for capturing, indexing, and correlating the real-time data and spark logs.
To apply: Visit www.envestnet.com/careers.
If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!