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Form of workJob Description
Description:
The Data Engineer will help build and maintain the cloud DeltaLake platform leveraging Databricks. Candidates will be expected to contribute to all stages of the data lifecycle including data ingestion, data modeling, data profiling, data quality, data transformation, data movement, and data curation. This job is located in-office at our World Headquarters in Kansas City.
Job Responsibilities may include:
Design, implement (deploy) and support on-premise and cloud-based data infrastructure (systems, flow) that are resilient to disruptions and failures
Enhance and support corporate SQL/NoSSQL database, DWH assets and streaming data solutions
Ensure high uptime for all data services and consider enhanced solutions through scheduled or event-driven design
Bring multi cloud/cross-platform agnostic technologies and practices into the system to enhance reliability and support rapid scaling of the business's data needs
Scale up our data infrastructure to meet cross-functional, multi industry business needs
Develop, leverage and maintain end-to-end data pipelines in production
Provide subject matter expertise and hands on delivery of data acquisition, curation and consumption pipelines on Azure, Databricks, AWS, Confluent
Responsible for maintaining current and emerging state of the art compute and cloud based solutions and technologies.
Build effective relationships with internal stakeholders
Familiarity with the technology stack available in the industry for metadata management: Data Governance, Data Quality, MDM, Lineage, Data Catalog etc.
Hands-on experience implementing analytics solutions leveraging Python, Spark SQL, Databricks Lakehouse Architecture, orchestration tools Kubernetes, Docker
ll other duties as assigned
Requirements:
Bachelor's degree in Computer Science, Information Technology, Management Information Systems (MIS), Data Science or related field. Applicable years of experience may be substituted for degree requirement.
Minimum 8 years of experience in software engineering
Experience with leading large and complex data projects, preferred
Experience with large-scale data warehousing architecture and data modeling, preferred
Worked with Cloud-based architecture such as Azure, AWS or Google Cloud, preferred
Experience working with big data technologies e.g. Snowflake, Redshift, Synapse, Postgres, Airflow, Kafka, Spark, DBT, preferred
Experience implementing pub/sub and streaming use cases, preferred
Experience leading design reviews, preferred
Experience influencing a team's technical and business strategy by making insightful contributions to team priorities and approaches, preferred
Working knowledge of relational databases, preferred
Expert in SQL, Python, Java and high-level languages such as Scala, C#, or C preferred
Demonstrate the ability to analyze large data sets to identify gaps and inconsistencies in ETL pipeline and provide solutions for pipeline reliability and data quality, preferred
Experience in designing and implementing an infrastructure as code / CICD development environment, preferred
Proven ability to build, manage and foster a team-oriented environment
Excellent communication (written and oral) and interpersonal skills
Excellent organizational, multi-tasking, and time-management skills
