ETL Engineer

We are looking fora seasoned
ETLEngineer to work with our team and our clients to develop enterprise grade data pipelines.

We are looking for more than just an"ETLEngineer", but a technologist with excellent communication and customer service skills and a passion for data and problem solving.

• Ability to obtain a government clearance, DOD Tier 3 clearance preferred
• Assess and understand ETL jobsandworkflows
• Create reusable data pipelines from source to target systems
• Test, validate, and deploy ETL pipelines
• Support reporting, business intelligence, and data science end users through ETL and ELT operations
• Work with data architects to create data models and design schemas for RDBMS, warehouse, and data lake systems
• Key must have skill sets – Python, SQL
• Work within an Agile software development lifecycle
• You will contribute to the growth of our Data Exploitation Practice!

• Required experience using Salesforce and Mulesoft
• Ability to hold a position of public trust with the US government.
• 2-4 years industry experience coding commercial software and a passion for solving complex problems.
• 2-4 years direct experience in Data Engineering with experience in tools such as:

• • ETL Tools:
    Python, Informatica, Pentaho, Talend
  • Big data tools:
    Hadoop, Spark, Kafka, etc.
  • Relational SQL and No
    
    SQL databases, including Postgres and Cassandra.
  • Data pipeline and workflow management tools:
    Azkaban, Luigi, Airflow, etc.
  • AWS cloud services: EC2, EMR, RDS, Redshift (or Azure equivalents)
  • Data streaming systems:
    Storm, Spark-Streaming, etc.
  • Search tools:
    Solr, Lucene, Elasticsearch
  • Object-oriented/object function scripting languages:
    Python, Java, C++, Scala, etc
  • CompTIA Network + preferred.

• Advanced working SQL knowledge and experience working with relational databases, query authoring and optimization (SQL) as well as working familiarity with a variety of databases.
• Experience with message queuing, stream processing, and highly scalable ‘big data’ data stores.
• Experience manipulating structured and unstructured data for analysis
• Experience constructing complex queries to analyze results using databases or in a data processing development environment
• Experience working in an Agile environment
• Experience supporting project teams of developers and data scientists who build web-based interfaces, dashboards, reports, and analytics/machine learning models