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Data Engineer

Kansas City, MO 64114

Posted: 07/10/2023 Employment Type: Contract to Hire Job Category: Database Technologies Job Number: 16154

Job Description

Adaptive Solutions Group is a premier provider of information technology personnel. We provide a variety of technical professionals available for contract, contract to hire, or direct placement positions to companies in and around the Kansas City and St. Louis areas.

We are currently looking for a Data Engineer to join our team.

  • Help build and maintain the cloud DeltaLake platform leveraging Databricks.
  • 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.
  • 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
Required Qualifications
  • 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.
  • 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.
Preferred Qualifications
  • Experience with leading large and complex data projects.
  • Experience with large-scale data warehousing architecture and data modeling.
  • Work with Cloud-based architecture such as Azure, AWS, or Google Cloud.
  • Experience working with big data technologies e.g., Snowflake, Redshift, Synapse, Postgres, Airflow, Kafka, Spark, DBT.
  • Experience implementing pub/sub and streaming use cases.
  • Experience leading design reviews.
  • Experience influencing a team’s technical and business strategy by making insightful contributions to team priorities and approaches.
  • Working knowledge of relational databases.
  • Expert in SQL, Python, Java, and high-level languages such as Scala, C#, or C.
  • 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.
  • Experience in designing and implementing an infrastructure as code / CICD development environment.
Adaptive Solutions Group offers a competitive compensation and benefits package that includes medical, dental, STD/LTD, life insurance coverage, 401k, paid vacation, and holidays.

Adaptive Solutions Group is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, and veteran or disability status.

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Abby Tryon

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