AI​/Data Engineer

Analytical Boost Inc. empowers individuals and organizations by providing tools, resources, and expertise to leverage data effectively. With over 20 years of experience, the company specializes in enterprise solutions, data analytics, forecasting models, and application development. Their innovative products, including AIM and PRISM, enable rapid data analysis, predictive insights, and performance optimization. They also offer customized application development, cloud solutions, and big data services to help customers access, store, and secure their data seamlessly.

Analytical Boost Inc. is dedicated to delivering tailored solutions and exceptional customer service.

This is a full‑time hybrid role for a AI/Data Engineer, based in Bentonville, AR, with the flexibility to work remotely on occasion. The Data Engineer will design, develop, and maintain data pipelines, architect and implement ETL processes, and support data warehousing solutions. The role involves collaborating with cross‑functional teams to ensure data accuracy, optimize data performance, and support data analytics initiatives.

Other responsibilities include identifying trends and patterns in datasets and providing actionable insights to meet business objectives.

• Design, build, and maintain reliable data pipelines that ingest, transform, and deliver data for analytics and operational use.
• Be Able to lead/support AI initiatives.
• Partner with customers/stakeholders to collect requirements, clarify definitions (metrics, dimensions, business rules), and translate needs into technical specifications.
• Write and optimize SQL for data extraction, transformation, validation, and performance tuning.
• Communicate requirements clearly to the development team; coordinate implementation details, sequencing, and acceptance criteria.
• Own delivery planning: estimates, milestones, risks, dependencies, and progress reporting; keep work moving across stakeholders.
• Implement data quality checks (completeness, accuracy, timeliness), reconcile across sources, and troubleshoot issues.
• Maintain documentation: source-to-target mappings, data dictionaries, pipeline logic, and runbooks.

• Strong database fundamentals: relational modeling, normalization/denormalization, indexing concepts, constraints, transactions, and query execution basics.
• AI/ML Knowledge
• Advanced SQL skills (joins, window functions, CTEs, aggregations, incremental logic, performance tuning).
• Proven experience mapping data sources and translating business logic into well‑defined transformations (source-to-target mapping).
• Demonstrated ability to gather requirements from customers (internal or external), manage expectations, and convert needs into clear technical tasks.
• Strong written and verbal communication—able to explain technical concepts to non‑technical audiences and vice versa.
• Project management capability: scoping, prioritization, timeline management, risk tracking, and cross‑team coordination.
• Comfortable working in agile environments (backlog grooming, sprint planning, demos, retros).

• Experience with AI/ML/Python
• Experience with ETL/ELT tooling
• Familiarity with cloud data platforms/warehouses (Snowflake, Big Query, Redshift, Databricks).
• Knowledge of data governance concepts (data lineage, access control, PII handling).

• 0–2 years of experience in data engineering, analytics engineering, BI development, or similar (internships/projects count).
• Bachelor’s degree in CS/IS/Engineering or equivalent hands‑on experience.

• Stakeholders trust the data and understand where it comes from (clear documentation + mapping).
• Pipelines run consistently with strong monitoring and quick incident resolution.
• Requirements are captured cleanly, delivered on time, and meet acceptance criteria with minimal rework