Data Product Engineer

To Apply for this Job

Role: Data Product Engineer.

Location: Remote.

Duration: Initial Term:
One-Year (Contract-To-Hire).

Start Date: November 3rd, 2025.

Eligibility: US Citizen.

Experience: At Least Ten Years.

Hours Per Week: 40 Hours.

We’re seeking a skilled Data Engineer to help design and implement scalable data solutions that power next-generation AI and analytics initiatives. In this role, you’ll work across multiple teams to create high-impact data products, modernize data ecosystems, and support automation and optimization efforts across complex technical environments. You’ll have the opportunity to shape data architecture, influence standards, and contribute directly to projects that drive measurable business outcomes.

• Perform data profiling and analysis across diverse data sources, including machine-generated and manually maintained data.
• Design and maintain ETL / ELT pipelines that ensure reliable and efficient data flow.
• Develop and manage metadata frameworks
  , data dictionaries
  , and business glossaries
  .
• Build logical and physical data models to support both transactional (OLTP) and analytical (OLAP) workloads.
• Implement data quality rules
  , schema evolution
  , and time travel strategies to ensure trust in data.
• Design multi-tenant, ACID-compliant table architectures for analytics and machine learning feature stores.
• Collaborate with stakeholders to gather requirements and build data products that support BI, AI, and ML applications.
• Analyze downstream system impacts and ensure data design aligns with enterprise architecture goals.

• Data Engineering: 2+ years of experience in distributed data processing (e.g., Spark, Databricks, EMR, or equivalent).
• Cloud Platforms: Hands-on experience with AWS or other cloud ecosystems (e.g., S3, Glue, Lambda, Redshift, Step Functions, EMR, Dynamo
  
  DB).
• Programming: Strong proficiency in Python (PySpark) and SQL for data transformation and automation.
• Data Platforms:
  
  Experience with Big Data technologies such as Hadoop, Spark, Hive
  , or No
  
  SQL engines (e.g., Cassandra, HBase).
• Experience implementing Apache Iceberg or Delta Lake architectures at scale, with familiarity in catalog integrations (Unity, Hive, Glue).
• Experience with RAG (Retrieval-Augmented Generation) and building data systems for AI/ML applications
  .
• Knowledge of data modeling tools (e.g., ERWin, ER/Studio) and concepts for graph databases and semantic ontologies
  .
• Familiarity with Enterprise Knowledge Graphs (EKG),
  SPARQL
  , OWL
  , and RDF
  .
• Exposure to data catalog and data lineage tools such as Alation or Unity Catalog.
• Understanding of lakehouse architectures and streaming vs. batch data processing.
• Strong troubleshooting skills and experience with performance tuning and data pipeline optimization
  .

• Strong communication and collaboration skills; ability to work effectively with technical and non-technical teams.
• Comfortable working in Agile environments and adapting to changing priorities.
• Team-oriented, ego-free mindset — eager to collaborate, share ideas, and continuously learn.

Equal Employment Opportunity Statement
Gravity IT Resources is an Equal Opportunity Employer. We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, veteran status, or any other legally protected characteristic. All employment decisions are based on qualifications, merit, and business needs.