BI Data Engineer III

McLane•Temple, TX

14d•Hybrid

About The Position

Moving America forward — together. We’ve been forging our path as a leader in the distribution industry since 1894. Building an expansive nationwide network of team members for 130+ years has allowed us to stay agile for our clients across the restaurant, retail, and e-commerce industries. We look to the future and are ready to continue making industry-defining moves by embracing the newest technology into our practices, continuing team member training, and emphasizing our people-centered culture. The Data Engineer III is a hybrid remote position which will require the candidate to report and work from the office three days a week. Therefore, interested candidates should be within a 50-minute radius from Temple, TX. Position Overview: Develop and maintain data processing software. Responsibilities include creating and optimizing data infrastructure, clean, prepare, and optimizes data for further analysis and modelling. Designs, develops, optimizes, and maintains data architecture and pipelines that adhere to Data Pipeline (i.e., ELT) principles and business goals. Lead complex data engineering projects and provide strategic guidance. Benefits you can count on: Day 1 Benefits\: medical, dental, and vision insurance, FSA/HSA, and company-paid life insurance Paid holidays, earn vacation time, and sick leave accrual from day one. 401(k) Profit Sharing Plan after 90 days. Additional benefits\: pet insurance, maternity/paternity leave, employee assistance programs, discount programs, tuition reimbursement program, and more!

Requirements

Bachelor’s degree in computer science, statistics, engineering, or a related field.
7 plus years of experience required.
Deep understanding of distributed computing, data architecture, and scalability.
Strong critical thinking skills and ability to address big data challenges.
Leadership and project management abilities.
Proficiency in designing and maintaining data warehouses and/or data lakes with big data technologies such as Spark/Databricks, or distributed databases, like Redshift and Snowflake, and experience with housing, accessing, and transforming data in a variety of relational databases.
Proficiency in building data pipelines and deploying/maintaining them following modern DE best practices (e.g., DBT, Airflow, Spark, Python OSS Data Ecosystem).
Proficiency in Software Engineering fundamentals and software development tooling (e.g., Git, CI/CD, JIRA) and familiarity with the Linux operating system and the Bash/Z shell.
Proficiency with cloud database technologies (e.g., Azure) and developing solutions on cloud computing services and infrastructure in the data and analytics space.
Basic familiarity with BI tools (e.g., Alteryx, Tableau, Power BI, Looker).
Expertise in ELT and data analysis, SQL primarily.
Conceptual knowledge of data and analytics, such as dimensional modelling, reporting tools, data governance, and structured and unstructured data.
This position requires the ability to read, write, and understand English at a level sufficient to perform job-related tasks effectively and safely. This includes understanding work instructions, safety protocols, and communications essential to the role. The requirement is directly related to the nature of the job and ensures compliance with workplace safety and operational standards.

Responsibilities

Designs, develops, optimizes, and maintains data architecture and pipelines that adhere to ELT principles and business goals.
Solves complex data problems to delivers insights that helps business achieve its goals.
Architect and implement end-to-end data solutions.
Define data engineering best practices and standards.
Mentor junior engineers and collaborate with cross-functional teams.
Creates data products for engineer, analyst, and data scientist team members to accelerate their productivity.
Engineer effective features for modelling in close collaboration with data scientists and businesses.
Leads the evaluation, implementation and deployment of emerging tools and process for analytics data engineering to improve productivity and quality.
Partners with machine learning engineers, BI, and solutions architects to develop technical architectures for strategic enterprise projects and initiatives.
Fosters a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions.
Advises, consults, mentors, and coach other data and analytic professionals on data standards and practices.
Develops and delivers communication and education plans on analytic data engineering capabilities, standards, and processes.
Understands machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics as necessary to conduct role effectively.
Performs other duties as assigned.