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Must Have Skills (Top 3 technical skills only)*:

Spark, Hive Python, Sqoop AWS

Detailed Job Description:

Advanced experience building cloud scalable, real time and high - performance data lake solutions leveraging AWS, EMR, EC2, S3, Spark, Hive & Lambda Experience with relational SQL, preferably Snowflake Experience with Python or another scripting language Experience with source control tools such as GitHub and related dev process Experience with Airflow or another scheduling tool Understanding of micro service architecture Strong understanding of developing complex data solutions Experience working on end-to-end solution design Experience preparing data to be analyzed and visualized (preferably with Tableau) Experience with Supply Chain a plus Experience with Attunity, DMS, Sqoop a plus Able to lead others in solving complex problems by taking a broad perspective to identify innovative solutions Willing to learn new skills and technologies Has a passion for data solutions Strong understanding of data structures and algorithms Strong understanding of solution and technical design Has a strong problem solving and analytical mindset Able to influence and communicate effectively, both verbally and written, with team members and business stakeholders Able to quickly pick up new programming languages, technologies, and frameworks

Responsibilities you would expect the Subcon to shoulder and execute*:

Help lead a team of data engineers, architects, and platform engineers to build innovative and sustainable data products that demonstrate business value Lead the design and build-out of reusable components, frameworks and libraries at scale to support analytics products Lead the design and implementation of product features in collaboration with business and technology stakeholders Anticipate, identify and solve issues concerning data management to improve data quality Help clean, prepare and optimize data at scale for ingestion and consumption Drive the implementation of new data management projects and refactoring of the current data architecture Help implement complex automated workflows and routines using workflow scheduling tools Lead the build-out of continuous integration, test-driven development and production deployment frameworks Drive collaborative reviews of design, code, test plans and dataset implementation performed by other data engineers in support of maintaining data engineering standards Analyze and profile data for the purpose of designing scalable solutions Troubleshoot complex data issues and perform root cause analysis to proactively resolve product and operational issues Mentor and develop data engineers in career development and adopting best practices