Data Solution Architect

Steampunk • McLean, VA

4d • $140,000 - $180,000

About The Position

Steampunk is seeking a seasoned Data Solution Architect to work with its team and clients to develop enterprise-grade data platforms, services, pipelines, data models, visualizations, and other data solutions. The role spans data vision and strategy through data science and calls for strong technical capabilities, communication and customer service skills, and a passion for data and problem solving.

The architect designs new data solution stacks in cloud or on-premises environments and plans migrations from legacy data environments with an emphasis on performance and reliability. Work covers data architecture, data engineering, business intelligence and visualization, and data science, including machine learning and AI applications and MLOps pipelines. The position also addresses technical questions about product customization, integration, enterprise architecture, features, and functionality; supports Agile software development; and contributes to the growth of Steampunk’s Data Exploitation Practice.

The projected annual salary range is $140,000 to $180,000. Applicants are expected to be on camera during interviews and assessments; Steampunk may take a picture to verify identity and prevent fraud. The role requires the ability to hold a position of public trust with the US government.

Requirements

• Ability to hold a position of public trust with the US government.
• At least 5 years of industry experience coding commercial software.
• At least 5 years of direct experience in Data Solutions.
• Broad understanding of the data exploitation lifecycle and its capabilities.
• Experience with big data tools such as Hadoop, Spark, and Kafka.
• Experience with relational SQL and NoSQL databases such as Postgres, MySQL, MS SQL Server, Oracle, and MongoDB.
• Experience with data pipeline and workflow management tools such as Airflow and NiFi.
• Experience with AWS cloud services such as EC2, EMR, RDS, Redshift, Glue, and SageMaker, or Azure and GCP equivalents.
• Experience with data streaming systems such as Storm and Spark Streaming.
• Experience with data science tools and languages such as R, RStudio, Python data preparation and analysis libraries, and Databricks.
• Experience with search tools such as Solr, Lucene, and Elasticsearch.
• Experience with object-oriented or scripting languages such as Python, Java, C++, and Scala.
• Advanced working SQL knowledge, including relational databases, query authoring and optimization, and familiarity with a variety of databases.
• Experience with DBOps and MLOps frameworks and exposure to or understanding of DevOps.
• Experience with message queuing, stream processing, and highly scalable big data stores.
• Experience manipulating, processing, and extracting value from large, disconnected datasets.
• Experience manipulating structured and unstructured data for analysis.
• Experience constructing complex queries to analyze results using databases or data-processing development environments.
• Experience with data modeling tools and processes.
• Experience architecting transactional and warehouse data systems.
• Experience aggregating results or compiling information for reporting from multiple datasets.
• Experience working in an Agile environment.
• Excellent communication and customer service skills, and a passion for data and problem solving.

Nice To Haves

• Experience crafting cloud data lakehouse solutions, preferably on AWS; Azure or GCP experience is also noted as an alternative.

Responsibilities

• Design greenfield data solution stacks in cloud or on-premises environments using current data services, products, technology, and industry best practices.
• Architect migrations from legacy data environments with attention to performance and reliability.
• Assess data sources, data models and schemas, and data workflows.
• Assess, understand, and design ETL jobs, data pipelines, and workflows.
• Assess and design reports, select BI tools, create dynamic dashboards, and establish pipelines that support dashboards and reports.
• Assess and design machine learning and AI applications, design MLOps pipelines, and support data scientists.
• Address technical inquiries about customization, integration, enterprise architecture, and data product features and functionality.
• Develop cloud data lakehouse solutions, including relational databases, data warehouses, data lakes, and distributed data systems.
• Support an Agile software development lifecycle.
• Contribute to the growth of Steampunk’s Data Exploitation Practice.
• Support project teams of developers and data scientists building web-based interfaces, dashboards, reports, analytics, and machine learning models.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed