Company Overview
This is your opportunity to join a highly respected, fast-growing IT and AI consultancy in Orange County — and actually grow with it. Whether you're stepping into your first professional tech role or you've got some experience under your belt, what matters most here is passion, hustle, and a genuine love for solving problems.
The Junior Data Engineer will support our IT and AI solutions by building and maintaining data pipelines, preparing data for AI and analytics workloads, supporting application-to-application data integrations, and ensuring reliable data flow between systems. This role is designed to evolve — as you grow, your responsibilities will expand into new areas of our technology and AI practice.
The Gig
The Junior Data Engineer will primarily focus on hands-on development work: building and supporting application-to-application data integrations, building and optimizing ETL pipelines, preparing structured and unstructured data for AI workloads, and assisting with cloud data services to ensure accurate, accessible data across the organization and our client environments. A secondary part of the role involves Power BI reporting and dashboard development to support business stakeholders.
This role blends data engineering with the emerging discipline of preparing data for AI — including data quality, structure, metadata, and pipelines that feed AI and machine learning systems. The position requires strong analytical skills, attention to detail, and the ability to communicate data-driven findings to both technical and non-technical audiences.
You'll be working alongside lead engineers who own the architecture and design decisions for our data platform and client environments. Your focus is on building, implementing, supporting, and operating what's been designed — with mentorship and guidance along the way.
We expect you to understand how programming works, know that best practices exist for a reason, and be hungry to learn the rest. You'll start with the core responsibilities below, but the scope will grow as you do — into new tools, new client environments, and new areas of the business, with a strong emphasis on AI-enablement work.
Key Responsibilities:
Application & Data Integration Development
- Build and maintain integrations between business applications (CRM, ERP, ticketing, finance, HR, and other line-of-business systems), following designs and patterns set by the senior data engineer.
- Implement integrations using APIs, webhooks, middleware, and integration platforms (e.g., Azure Logic Apps, Power Automate, Azure Function Apps, or similar iPaaS tools).
- Map data between source and destination systems, handling field-level transformations, data type mismatches, and sync rules as specified.
- Troubleshoot integration issues, resolve data-flow errors, and ensure consistent, accurate data exchange across connected applications.
- Monitor integration health, build alerting where appropriate, and implement improvements for efficiency and reliability.
- Document integrations, data mappings, and maintenance procedures.
ETL Development & AI and Reporting Data Readiness
- Implement and optimize ETL/ELT workflows to extract, transform, and load data across multiple systems, based on designs from the senior data engineer.
- Build and maintain cloud-based data pipelines using Azure Data Factory and Azure Synapse Analytics.
- Prepare and curate data for AI and machine learning use cases — including cleaning, normalizing, enriching, and structuring data so it's ready for downstream AI workloads (RAG pipelines, embeddings, model training, semantic search, etc.).
- Work with both structured and unstructured data sources (databases, documents, APIs, files) and apply techniques like chunking, metadata tagging, and deduplication to make data AI-consumable.
- Validate ETL processes for accuracy, performance, and AI-readiness, ensuring they meet business, reporting, and AI requirements.
- Document pipeline logic, workflows, and maintenance procedures for long-term support.
SQL Management & Data Engineering
- Write and execute SQL queries to extract, transform, and analyze data for engineering, reporting, and AI use cases.
- Build and maintain views, stored procedures, and datasets that feed downstream systems including Power BI and AI/ML pipelines.
- Validate data quality, identify anomalies, and support troubleshooting across data sources.
DevOps Practices
- Assist with code deployments, pipeline monitoring, and troubleshooting build or release failures.
- Follow established version control practices and contribute to maintaining clean, well-documented codebases.
Power BI Reporting & Dashboard Development
- Build and maintain BI dashboards and reports that surface key business metrics, working from requirements provided by stakeholders and guidance from the senior data engineer.
- Develop DAX measures and calculated columns to support reporting needs.
- Build data models within Power BI that connect multiple data sources into a unified view, following patterns established by the senior team.
- Publish, schedule, and manage reports within the Power BI Service, including row-level security and workspace governance.
- Collaborate with stakeholders to translate business questions into clear, visual data stories.
Client-Facing Support & Communication
- Work with IT colleagues and business stakeholders to clarify requirements, data definitions, and workflow expectations.
- Provide technical guidance in plain language and help translate business needs into technical solutions.
- Assist end users with reporting and general data inquiries across client environments.
- Create and maintain user-facing documentation, including release notes, how-to guides, and process walkthroughs.
Objectives of the Role
- Build and maintain reliable application integrations that keep data synchronized and trustworthy across the systems our business and our clients depend on.
- Build and maintain ETL pipelines — including cloud-based workflows in Azure Data Factory and Synapse Analytics — that ensure clean, reliable data across systems.
- Help prepare data for AI and machine learning use cases, ensuring it's structured, clean, and ready for downstream consumption.
- Ensure data accuracy, consistency, and integrity across all engineering, reporting, and AI touchpoints.
- Deliver BI dashboards and reports that give stakeholders timely, trustworthy insights.
- Troubleshoot data, pipeline, and integration issues with guidance from the senior data engineer.
- Communicate technical and analytical information clearly to both technical and non-technical team members.
- Grow into expanded responsibilities — particularly around AI-enablement — as the role and the business evolve.
Desired Skills & Qualifications
Required
- Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field.
- Strong SQL skills and experience working with relational databases.
- Familiarity with version control systems (e.g., Git).
- Familiarity with ETL/ELT concepts and exposure to building data workflows (coursework, internships, personal projects, or hands-on work count).
- Familiarity with Python (or a similar language) for data manipulation and scripting.
- Familiarity with APIs, RESTful services, and structured data formats (e.g., JSON, XML).
- Ability to exercise good judgement with supervision on moderately complex data tasks.
- Effective communication skills for explaining data insights and technical processes to diverse audiences.
- Strong analytical thinking, problem-solving skills, and attention to detail.
Preferred
- Hands-on experience building ETL/ELT pipelines in production environments.
- Experience with Azure Data Factory, Azure Synapse Analytics, or similar cloud data services.
- Experience building or supporting integrations between business applications using APIs, webhooks, or integration/middleware platforms.
- Experience with iPaaS or workflow automation tools (Azure Logic Apps, Power Automate, Azure Function Apps, Workato, Zapier, Make, or similar).
- Familiarity with common business application APIs (e.g., Microsoft 365, Salesforce, HubSpot, NetSuite, ServiceNow, Halo, ConnectWise, or similar).
- Exposure to AI/ML concepts — vector databases, embeddings, RAG (retrieval-augmented generation), or preparing data for LLM-based applications.
- Experience working with unstructured data (documents, transcripts, knowledge bases) and preparing it for downstream consumption.
- Experience with Power BI Service administration, row-level security, or dataflows.
Role Characteristics
- Works under general and technical supervision with good latitude for independent judgment on implementation work.
- Regular collaboration with IT staff, stakeholders, and end users to deliver data-driven solutions.
- Scope of the role will expand over time as skills develop and business needs grow.
Pay: $65,000.00 - $75,000.00 per year
Benefits:
- 401(k)
- 401(k) matching
- Dental insurance
- Flexible schedule
- Health insurance
- Health savings account
- Paid time off
- Retirement plan
Work Location: In person
