Salesforce Technical Lead

steampunk•McLean, VA

2d•$150,000 - $200,000

About The Position

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. 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 a seasoned Technical Lead to work with our team and our clients to develop enterprise grade data platforms, services, pipelines, data models, visualizations, and more! The Tech Lead needs to be a technologist with excellent communication and customer service skills and a passion for data and problem solving. This role involves technical and thought leadership across the spectrum of data capabilities, from data vision and strategy all the way through data science. Designing and leading the implementation of greenfield data solution stacks in the cloud or on premises, using the latest data services, products, technology, and industry best practices Architecting and leading the migration of legacy data environments with performance and reliability Data Architecture contributions include assessing, understanding, and implementing data sources, data models and schemas, and data workflows Data Engineering contributions include assessing, understanding, designing, and implementing ETL jobs, data pipelines, and workflows BI and Data Visualization contributions include assessing, understanding, designing, and implementing reports, selecting BI tools, creating dynamic dashboards, and setting up data pipelines in support of dashboards and reports Data Science contributions include assessing, understanding, designing, and implementing machine learning and AI applications, designing MLOps pipelines, and supporting data scientists Addressing technical inquiries concerning customization, integration, enterprise architecture and general feature / functionality of data products Experience in crafting and implementing data lakehouse solutions in the cloud (Preferably AWS. Alternatively, Azure, GCP). This includes relational databases, data warehouses, data lakes, and distributed data systems. Key must have skill sets – broad understanding of data exploitation lifecycle and capabilities, technical leadership in the data field Support an Agile software development lifecycle

Requirements

Ability to obtain and hold a security clearance with the US government.
5+ years industry experience leading the design and implementation of data systems
5+ years direct experience in Data Solutions with experience in tools such as:
Big data tools: Hadoop, Spark, Kafka, etc.
Relational SQL and NoSQL databases, such as Postgres, MySQL, MS SQL Server, Oracle, Mongo, etc.
Data pipeline and workflow management tools: Airflow, NiFi, etc.
AWS cloud services such as EC2, EMR, RDS, Redshift, Glue, SageMaker (or Azure and GCP equivalents)
Data streaming systems: Storm, Spark-Streaming, etc.
Data science tools/languages: R, R Studio, Python (data preparation and analysis libraries), Databricks, etc.
Search tools: Solr, Lucene, Elasticsearch
Object-oriented/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 DBOps and MLOps frameworks and exposure/understanding of DevOps
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 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

Responsibilities

Designing and leading the implementation of greenfield data solution stacks in the cloud or on premises, using the latest data services, products, technology, and industry best practices
Architecting and leading the migration of legacy data environments with performance and reliability
Data Architecture contributions include assessing, understanding, and implementing data sources, data models and schemas, and data workflows
Data Engineering contributions include assessing, understanding, designing, and implementing ETL jobs, data pipelines, and workflows
BI and Data Visualization contributions include assessing, understanding, designing, and implementing reports, selecting BI tools, creating dynamic dashboards, and setting up data pipelines in support of dashboards and reports
Data Science contributions include assessing, understanding, designing, and implementing machine learning and AI applications, designing MLOps pipelines, and supporting data scientists
Addressing technical inquiries concerning customization, integration, enterprise architecture and general feature / functionality of data products
Experience in crafting and implementing data lakehouse solutions in the cloud (Preferably AWS. Alternatively, Azure, GCP). This includes relational databases, data warehouses, data lakes, and distributed data systems.
Key must have skill sets – broad understanding of data exploitation lifecycle and capabilities, technical leadership in the data field
Support an Agile software development lifecycle