Data Engineer

Key Skills

Amazon Elastic Compute Cloud-EC2, Amazon EMR, Amazon RDS, Amazon RedShift, Apache Airflow, Apache Hadoop, Apache Kafka, AWS, Azure, C++, Google Cloud Platform (GCP), Java Programming, Object-Oriented programming (OO languages), Python Programming, Scala Programming, SPARK Programming, SQL

Job Description

Overview

In today’s rapidly evolving technology landscape, an organization’s data has never been a more important aspect in achieving mission and business goals. Our data exploitation experts work with our clients to support their mission and business goals by creating and executing a comprehensive data strategy using the best technology and techniques, given the challenge.

At Steampunk, our goal is to build and execute a data strategy for our clients to coordinate data collection and generation, to align the organization and its data assets in support of the mission, and ultimately to realize mission goals with the strongest effectiveness possible.

For our clients, data is a strategic asset. They are looking to become a facts-based, data-driven, customer-focused organization. To help realize this goal, they are leveraging visual analytics platforms to analyze, visualize, and share information. At Steampunk you will design and develop solutions to high-impact, complex data problems, working with the best and data practitioners around. Our data exploitation approach is tightly integrated with Human-Centered Design and DevSecOps.

Contributions

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 a more than just a Data Engineer, but a technologist with excellent communication and customer service skills and a passion for data and problem solving.

• Lead and architect migration of data environments with 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, AWS
• Support an Agile software development lifecycle
• You will contribute to the growth of our Data Exploitation Practice!

Qualifications

• US Citizen Only
• Ability to hold a position of public trust with the US government.
• 5+ years industry experience coding commercial software and a passion for solving complex problems.
• 5+ 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, 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.
• 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, processing, and extracting value from large, disconnected datasets.
• Eperience manipulating structured and unstructured data for analysis
• Experience constructing complex queries to analyze results using databases or in a data processing development environment
• Experience with data modeling tools and process
• Experience architecting data systems (transactional and warehouses)
• Experience aggregating results and/or compiling information for reporting from multiple datasets
• 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