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Data Engineer - Databricks

$110k - $160k

Steampunk

Overview

We are looking for seasoned Data Engineer to work with our team and our clients to develop enterprise grade data platforms, services, and pipelines. We are looking for more than just a "Data Engineer", but a technologist with excellent communication and customer service skills and a passion for data and problem solving.

Contributions

  • Lead and architect data pipelines and ingest patterns to move raw data from data producers to an enterprise data ecosystem, with a focus on performance and reliability
  • Assess and understand the ETL jobs, workflows, BI tools, and reports
  • Address technical inquiries concerning customization, integration, enterprise architecture and general feature / functionality of data products
  • Experience in crafting database / data warehouse solutions in cloud (Preferably AWS. Alternatively Azure, GCP).
  • Key must have skill sets – Python, SQL, Databricks, AWS Data Services
  • Support an Agile software development lifecycle
  • You will contribute to the growth of our Data Exploitation Practice!

Qualifications

  • Experience supporting ICE contract work.
  • Experience working in Design Intelligence. 
  • Bachelor’s Degree and 6+ years of total experience or equivalent experience and education.
  • 6+ years direct experience in Data Engineering with experience in tools such as:
    • Big data tools: Hadoop, Spark, Kafka, etc.
    • Relational SQL and NoSQL databases, including Postgres and Cassandra.
    • Data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
    • AWS cloud services: EC2, S3, RDS, Glue, Step Functions, Lamda, EMR, DynamoDB, DocumentDB, Redshift, Aurora, Athena
    • Data Platforms: Databricks, Snowflake
    • Data streaming systems: Kafka, Storm, Spark-Streaming, etc.
    • Languages: Python, R, Scala, Go
  • Ability to inspect existing data pipelines, discern their purpose and functionality, and re-implement them efficiently in Databricks.
  • Advanced working SQL knowledge and experience working with relational databases
  • Advanced working knowledge and of NoSQL databases
  • Experience with message queuing, stream processing, and highly scalable ‘big data’ data stores.
  • Experience manipulating, processing, and extracting value from large, disconnected datasets.
  • Experience manipulating structured and unstructured data for analysis.
  • Experience with data modeling tools and processes.
  • Experience aggregating and transforming data from multiple datasets to create data products
  • Experience working in an Agile environment

About steampunk

Steampunk relies on several factors to determine salary, including but not limited to geographic location, contractual requirements, education, knowledge, skills, competencies, and experience. The projected compensation range for this position is $110,000 to $160,000. The estimate displayed represents a typical annual salary range for this position. Annual salary is just one aspect of Steampunk’s total compensation package for employees. Learn more about additional Steampunk benefits here. 

 

Identity Statement

As part of the application process, you are expected to be on camera during interviews and assessments. We reserve the right to take your picture to verify your identity and prevent fraud.

 

Steampunk is a Change Agent in the Federal contracting industry, bringing new thinking to clients in the Homeland, Federal Civilian, Health and DoD sectors. Through our Human-Centered delivery methodology , we are fundamentally changing the expectations our Federal clients have for true shared accountability in solving their toughest mission challenges. If you want to learn more about our story, visit

 

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law. Steampunk participates in the E-Verify program.  

Vacancy posted 9 days ago
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