Data Engineer III - Hybrid Position
(Requires 1 day per week in either OKC or Grapevine, TX Office)
This position will be located within the Development and IT space and work closely with computer scientists, IT and data scientists to build, deploy and optimize data pipelines and integrate data infrastructure for enabling analytics, reporting, and machine learning workloads at scale.
Build, test, and validate robust production-grade data pipelines that can ingest, aggregate, and transform large datasets according to the specifications of the internal teams who will be consuming the data
Build frameworks and custom tooling for data pipeline code development
Deploy data pipelines and data connectors to production environments
Configure connections to source data systems and validates schema definitions with the teams responsible for the source data
Monitor data pipelines and data connectors and troubleshoot issues as the arise
Monitor data lake environment for performance and data integrity
Manage data infrastructure such as Kafka and Kubernetes clusters
Collaborate with IT and database teams to maintain the overall data ecosystem
Assist data science, business intelligence, and other teams in using the data provided by the data pipelines
Mentor junior data engineers
Deploy machine learning models to production environments
Gather requirements and determine scope of new projects
Research and evaluate new technologies and set up proof-of-concept deployments
Test proof-of-concept deployments of new technologies
Collaborate with data governance and compliance teams to ensure data pipelines and data storage environments meet requirements
Serve as on-call for production issues related to data pipelines and other data infrastructure maintained by the data engineering team
MINIMUM BASIC QUALIFICATIONS
BS degree in Computer Science or related field
5+ years of data engineering work experience
Experience with ETL and ELT processes in data pipelines
Experience with Apache Spark or Databricks and reading and writing Parquet, Avro and JSON
Experience coding in Java or Scala and build tools such as Maven, Gradle, and SBT is required
Experience with SQL databases
Experience coding in Java or Scala and build tools, Maven, Gradle and SBT
Experience with CICD tools and processes
Experience working with HDFS or S3 storage environments
Experience working in a Unix or Linux environment including writing shell scripts
Experience coding in Python
Experience with NoSQL solutions
Experience with Apache Kafka or Confluent is highly preferred
Experience with data lake query engines such as Presto or Dremio
Experience with Docker and Kubernetes highly preferred
Experience with workflow orchestration tools like Apache Airflow, Control-M, or Arrow highly preferred
Skills and Abilities:
Strong expertise in computer science fundamentals: data structures, performance complexities, algorithms, and implications of computer architecture on software performance such as I/O and memory tuning.
Working knowledge software engineering fundamentals: version control systems such as Git and Github, workflows, ability to write production-ready code.
Knowledge of data architecture and data processing engines such as Spark and Hadoop.
Ability to create SQL queries of moderate complexity.
Knowledge of Java or Scala.
Knowledge of Apache Spark
Knowledge of Python, R, C#, or PHP is helpful.
Knowledge of HDFS and S3 storage environments
Strong trouble-shooting skills.
Knowledge of technical infrastructure.
Strong technical aptitude.
Has strong critical thinking skills and the ability to relate them to the products.
Demonstrates excellent verbal and written communication skills.