Senior Data Engineers

CCC Intelligent Solutions•Chicago, IL

3d•$108,077 - $125,282•Remote

About The Position

CCC Intelligent Solutions Inc. (CCC) is a leading cloud platform for the multi-trillion-dollar insurance economy, creating intelligent experiences for insurers, repairers, automakers, part suppliers, and more. At CCC, we’re making life just work by empowering more than 35,000 businesses with industry-leading technology to get drivers back on the road and to health quickly and seamlessly. We’re pushing boundaries with innovative AI solutions that simplify and enhance the claims and repair journey. Through purposeful innovation and the strength of its connections, CCC technologies empower the people and industry relied upon to keep lives moving forward when it matters most. Learn more about CCC at www.cccis.com. The Role Key Responsibilities: Senior Data Engineers for various and unanticipated worksites throughout the U.S. (HQ: Chicago, IL). Develop large scale end to end data pipeline applications, covering multiple data sources spread across data center and AWS cloud. Use developed software applications to locate and analyze source data; create data flows to extract, profile, and store ingested data; define and build data cleansing and imputation; map to a common data model; transform to satisfy business rules and statistical computations; and validate data content. Produce software data building blocks, data models, and data flows, such as dimensional data, data feeds, dashboard reporting, and data science research and exploration. Produce automated software tests of data flow components and for data content quality. Automate orchestration and error handling for use by production operation teams. Provide technical expertise to diagnose errors from production support teams. Guide junior team members in performance tuning applications in distributed computing environments. Perform root cause analysis on all data and processes and identify opportunities for improvement. Develop metadata-driven and fully parameterized data processing tools. Mentor junior engineers. Technical Environment: Programming using Python & PySpark; Hadoop; HDFS, map-reduce, YARN, AWS EMR, Redshift, Terraform; Hive, HBase, parquet, ORC, Spark SQL, Sqoop, Apache Hudi; Orchestrating ETL pipelines involving data sourcing, transformations & publishing using Apache Airflow; Performance tuning applications in distributed computing environments; Designing & developing data pipeline applications with Apache Kafka; Advanced SQL for data profiling & data validation; Unix commands & scripting; performing root cause analysis on internal & external data & processes to identify opportunities for improvement; JIRA, Gitlab, Subversion; Development of metadata-driven & fully parameterized data processing tools; AWS. #LI-DNI #NOINDEED

Requirements

Master’s degree in Computer Science, Computer Engineering, Management Information Systems or related field plus 2 years of experience in software development/data processing or analysis required.
Hands-on experience with: Programming using Python & PySpark; Hadoop; HDFS, map-reduce, YARN, AWS EMR, Redshift, Terraform; Hive, HBase, parquet, ORC, Spark SQL, Sqoop, Apache Hudi; Orchestrating ETL pipelines involving data sourcing, transformations & publishing using Apache Airflow; Performance tuning applications in distributed computing environments; Designing & developing data pipeline applications with Apache Kafka; Advanced SQL for data profiling & data validation; Unix commands & scripting; performing root cause analysis on internal & external data & processes to identify opportunities for improvement; JIRA, Gitlab, Subversion; Development of metadata-driven & fully parameterized data processing tools; AWS.

Responsibilities

Develop large scale end to end data pipeline applications, covering multiple data sources spread across data center and AWS cloud.
Use developed software applications to locate and analyze source data; create data flows to extract, profile, and store ingested data; define and build data cleansing and imputation; map to a common data model; transform to satisfy business rules and statistical computations; and validate data content.
Produce software data building blocks, data models, and data flows, such as dimensional data, data feeds, dashboard reporting, and data science research and exploration.
Produce automated software tests of data flow components and for data content quality.
Automate orchestration and error handling for use by production operation teams.
Provide technical expertise to diagnose errors from production support teams.
Guide junior team members in performance tuning applications in distributed computing environments.
Perform root cause analysis on all data and processes and identify opportunities for improvement.
Develop metadata-driven and fully parameterized data processing tools.
Mentor junior engineers.