Staff Data Engineer

Role Overview:

The Staff Data Engineer independently plans, schedules, and leads data, analytics, and business intelligence projects of moderate scope or portions of major large-scale projects, and participates in the determination of technical objectives. Responsible for the department's data integration work, including developing a data model, maintaining a data warehouse and analytics environment, and writing scripts for data integration and analysis. This role will work closely and collaboratively with members of the Data & Analytics and other development teams to define requirements, mine and analyze data, integrate data from a variety of sources, and deploy high quality data pipelines in support of the analytics needs of the organization.

Role 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 site 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. Responsible for organizing data and preparing documentation for assigned projects.
• Responsible for thoroughly testing 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. Closer supervision given on new aspects of assignments.

Qualifications:

• At least ten years of relevant data, analytics, and BI engineering experience
• BS degree in related field or equivalent work experience
• 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, clean it, transform, and recode it, merge different data sets together, reformat data between wide and long, etc.
• Ability to learn new techniques and troubleshooting code without support, in other words, be able to learn on the job.
• Use APIs to push and pull data from various data systems and platforms.
• 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.

Preferred Qualifications:

• Experience with Azure environment
• Experience developing cloud data warehouses (e.g. Snowflake or Databricks)
• Experience with lambda and kappa architecture
• Experience with iPaaS platforms and other no-code/low-code platforms