Senior Data Engineer (P4086)

84.51; Chicago (IL); On-site; USD 100,000 - 130,000; Full time

Job summary

84.51 in Chicago is seeking a Senior Data Engineer to build solutions for big data that will be utilized by data scientists and various products. You will work with tools like PySpark, Databricks, and Hadoop to deliver vital data capabilities.

Key responsibilities include developing cloud-based solutions and providing mentorship to junior staff. Ideal candidates will have over 4 years of experience in data development and strong skills in data engineering technologies.

Qualifications

• 4+ years proven ability of professional Data Development experience.
• 3+ years proven ability of developing with Databricks or Hadoop/HDFS.
• 3+ years of experience with PySpark/Spark.
• 3+ years of experience with SQL.
• Full understanding of ETL concepts and Data Warehousing concepts.

Responsibilities

• Take ownership of features and drive them to completion through all phases.
• Participate in the design and development of Databricks and Cloud-based solutions.
• Implement automated unit and integration testing.
• Collaborate with architecture and lead engineers on development practices.
• Provide mentoring to junior engineers.

Skills

Data Development

Databricks

Hadoop/HDFS

PySpark/Spark

SQL

Python

Java

Scala

Agile Principles

Education

Bachelor’s Degree in Computer Science or related fields

Tools

Databricks

Hadoop

GitHub

Job description

As a Senior Data Engineer, you will have the opportunity to build solutions that ingest, transform, store, and distribute our big data to be consumed by data scientists and our products.

Our data engineers use PySpark/Python, Databricks, Hadoop, Hive, and other data engineering technologies and visualization tools to deliver data capabilities and services to our scientists, products, and tools.

Responsibilities

Take ownership of features and drive them to completion through all phases of the entire 84.51° SDLC. This includes internal and external facing applications as well as process improvement activities:

• Participate in the design and development of Databricks and Cloud-based solutions.
• Implement automated unit and integration testing.
• Collaborate with architecture and lead engineers to ensure consistent development practices.
• Provide mentoring to junior engineers.
• Participate in retrospective reviews.
• Participate in the estimation process for new work and releases.
• Collaborate with other engineers to solve and bring new perspectives to complex problems.
• Drive improvements in data engineering practices, procedures, and ways of working.
• Embrace new technologies and an ever-changing environment.

Requirements

• 4+ years proven ability of professional Data Development experience
• 3+ years proven ability of developing with Databricks or Hadoop/HDFS
• 3+ years of experience with PySpark/Spark
• 3+ years of experience with SQL
• 3+ years of experience developing with either Python, Java, or Scala
• Full understanding of ETL concepts and Data Warehousing concepts
• Experience with CI/CD
• Experience with version control software
• Strong understanding of Agile Principles (Scrum)
• Bachelor’s Degree (Computer Science, Management Information Systems, Mathematics, Business Analytics, or STEM)

Bonus Points

• Experience with Azure
• Experience with Databricks Delta Tables, Delta Lake, Delta Live Tables
• Proficient with Relational Data Modeling
• Experience with Python Library Development
• Experience with Structured Streaming (Spark or otherwise)
• Experience with Kafka and/or Azure Event Hub
• Experience with GitHub SaaS / GitHub Actions
• Experience with Snowflake
• Exposure to BI Tooling (Tableau, Power BI, Cognos, etc.)