Data Engineer

betterdebtsolutions; Irvine (CA); On-site; USD 140,000 - 155,000; Full time

Job summary

Better Companies is seeking a Data Engineer to design and optimize an enterprise data platform centered on Microsoft Fabric and lakehouse architecture. You will build reliable ingestion pipelines, model data, and ensure freshness and accuracy for operational reporting and AI-driven insights.

The role emphasizes end-to-end data reliability, performance tuning, and collaboration with analytics and BI teams, with an in-office Irvine base and a competitive salary.

Qualifications

• Strong proficiency in Python, PySpark, and advanced SQL.
• Experience with data warehouse and lakehouse architectures.

Responsibilities

• Design and implement scalable data warehouse and Lakehouse architectures using Microsoft Fabric and Azure.
• Architect data structures with OneLake, Fabric Warehouse, and Lakehouse (bronze, silver, gold).
• Develop and maintain ingestion and transformation pipelines using Data Factory in Fabric and Spark/Python notebooks.
• Ingest data from REST APIs and relational databases (MySQL/MariaDB, PostgreSQL/Redshift, SQL Server).
• Design dimensional models and star schemas with SCD Type 2 history and conformed dimensions.
• Centralize business logic in gold-layer tables for consistent semantic models feeding dashboards.

Skills

Python

PySpark

Advanced SQL

Git-based development

Education

Bachelor's degree in Computer Science, Data Science, Information Systems, or related field

Tools

Azure Data Factory

Microsoft Fabric

Delta Tables

Azure DevOps

GitHub

Job description

Better Companies is a multi-brand financial services organization providing debt relief, tax support, and business funding solutions. We're strengthening our operations, refining our systems, and building a more cohesive, efficient experience across our brands. Our approach is grounded in transparency, strong operational foundations, and well-structured processes that support reliable execution and scalable growth.

About the Role

We are seeking an experienced Data Engineer to design, build, support, and optimize our modern enterprise data platform . In this role, you will modernize our data architecture toward a Microsoft Fabric-based environment, developing reliable ingestion pipelines and modeling data into trusted lakehouse and warehouse layers . A key focus of the position involves accelerating data transformation performance and maximizing the efficiency of Fabric capacity utilization . You will take ownership of end-to-end data reliability, ensuring the freshness, completeness, and accuracy of data required for operational reporting and AI-driven insights . If you are solutions-oriented, thrive on ambiguity, and take pride in turning complex data problems into reliable systems, we'd love to have you on our team .

Location

Irvine, CA (Fully In-Office)

Compensation

$140,000 - $155,000 / year

Job Type

Full-Time (Exempt/Salary)

What You'll Be Doing

In this role, priorities can shift rapidly based on system optimization needs, business analytics demands, and strategic platform initiatives .

Data Platform Architecture & Lakehouse Engineering

Design and implement scalable data warehouse and Lakehouse architectures utilizing Microsoft Fabric and Azure .

Architect and organize data structures within OneLake, Fabric Warehouse, and Lakehouse using a medallion (bronze, silver, gold) approach .

Develop and maintain ingestion and transformation pipelines using Data Factory in Fabric (pipelines, Copy jobs) and Spark/Python notebooks .

Ingest data from REST APIs and relational databases (MySQL/MariaDB, PostgreSQL/Redshift, SQL Server), including sources operating behind on-premises data gateways .

Design dimensional models and star schemas with SCD Type 2 history and conformed dimensions to support cross-functional reporting .

Centralize business logic in curated gold-layer tables to ensure semantic models remain consistent and feed near-real-time operational dashboards .

Performance Tuning & Capacity Optimization

Profile and tune Spark and SQL workloads to accelerate transformation run times via partitioning, file sizing, join strategies, and caching .

Redesign legacy full-reload processes into incremental and change-data-capture (CDC) pipelines to minimize compute overhead .

Monitor and manage Fabric capacity (CU) consumption with the Fabric Capacity Metrics app to prevent compute throttling during peak workloads .

Maintain Delta tables using OPTIMIZE, VACUUM, and V-Order to ensure fast read performance in Direct Lake and warehouse queries .

Audit existing pipelines, notebooks, and dataflows to eliminate redundant processing and consolidate duplicate logic .

Data Reliability, Observability & Stakeholder Collaboration

Implement automated freshness, volume, and completeness monitoring alongside proactive alerting on all production pipelines .

Reconcile loaded data against source systems to resolve ingestion gaps and anomalies at the root cause .

Execute safe historical data corrections and backfills with dry runs and validation prior to deploying to production .

Collaborate closely with vendor partners, internal business users, BI, and analytics teams to deliver cost-efficient, scalable data solutions .

Who You Are

We value adaptability, a solutions-oriented mindset, and deep technical curiosity :

• Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field (or equivalent professional experience) .
• 7+ years of hands-on experience in Data Engineering or Data Platform Development, including direct production experience with Microsoft Fabric and Azure data technologies .
• Proven ability to identify, decompose, and solve complex data challenges independently and as part of a team . You adapt smoothly to shifting priorities, take initiative in fast-paced environments, and maintain resilience when troubleshooting intricate system issues .
• Strong proficiency in Python, PySpark, and advanced SQL . Proven track record of reducing run times and compute costs through workload optimization, incremental loading, and dimensional modeling (star schema, SCD Type 2) .
• Practical experience with Git-based development and deployment promotion workflows using Azure DevOps or GitHub .
• Excellent communicator with the ability to bridge conversations across executive leadership (CFO, COO), vendor partners, and non-technical stakeholders alike .

Bonus Points (Great to Have)

• Microsoft Fabric Data Engineer Associate (DP-700) certification .
• Familiarity with Azure AI Foundry o