Data Engineer, Staff

Job Duties And Responsibilities

• Designs and builds multi-tenant systems capable of loading and transforming large volumes of structured and semi-structured fast-moving data.
• Works with Program and Project Managers to understand the features, do technical assessment, design, code, test and deliver.
• Defines and manages SLAs and data quality for datasets and processes.
• Designs, implements, tests, deploys, and maintains stable, secure, and scalable data engineering solutions and pipelines in support of data and analytics projects, including integrating new sources of data into our central data warehouse, and moving data out to applications.
• Independently works on a wide range of complex problems that require new approaches through adaptation and modification of standard data, analytics, and BI principles, theories, techniques, and procedures, providing solutions that are imaginative, thorough, and practical.
• Develops new and varied solutions to data, analytics, and BI projects and contributes to the value of program solutions by studying industry best practices, seeking to understand and validate internal customer needs, and supporting line of sight of program execution to business impacting.
• Performs one-off data manipulation/munging and analysis on a wide variety organizing data.
• Implements and monitors best in class security measures in our data warehouse and analytics environment, with an eye towards the evolving threat landscape.
• Analyzes data, analytics, and BI problems to determine suitable solutions.
• Establishes and coordinates design reviews with peers and project leads.
• Organizes data and prepares documentation for assigned projects.
• Tests thoroughly their data, analytics, and BI solutions, coordinating others on data, analytics, and BI verification tests, and testing peer data, analytics, and BI solutions when necessary.
• Most work examined at a higher level. Actual supervision received may be minimal or moderate depending upon project complexity.

Qualifications

• Strong command of best practices applied in relational databases and SQL as well as Extract, Transform, and Load (ETL) data into a relational database.
• Deep understanding Data Warehousing, Date Lakes, Date Pipelines, and Business Intelligence Applications.
• Ability to interpret moderately complex data, analytics, and BI requirements and apply data, analytics, and BI design methodologies.
• General data manipulation skills: read in data, process, and clean it, transform, and recode it, merge different data sets together, reformat data between wide and long, etc.
• Ability to learn new techniques and troubleshoot code without support, in other words, be able to learn on the job.
• Ability to write clear code that is well-documented and stored in a version control system.
• Proficient with Python, databases, and SQL expertise.
• Proven ability to work both independently and collaboratively within a team environment while following established procedures.
• Excellent listening, interpersonal, communication and problem-solving skills.