Data Engineer

Associa • Richardson, TX

2h • Hybrid

About The Position

We are seeking an experienced Data Engineer to join our team and lead data
migration efforts through the development and optimization of our data platform.
This role is critical to designing and executing dynamic, scalable data
extraction and ingestion pipelines, implementing robust ingestion frameworks,
and enabling analytics and data science initiatives across the organization. 
The candidate must have expert, hands-on experience in Python, Databricks, SQL,
and a proven track record of designing and implementing enterprise-grade data
ingestion solutions.  Must be local to the Dallas/Ft Worth area - will require
some onsite presence at our Richardson, TX location.

Requirements

• Big Data Platforms: Direct, hands-on experience building and operating Databricks-based data platforms, including Unity Catalog, Delta Lake, Delta Live Tables (DLT), Workflows, and Apache Spark.
• Python: Strong to Expert proficiency required, Deep understanding of Python for data engineering (PySpark, pandas, or equivalent), data validation in pipelines (e.g. Pydantic, Great Expectations, or equivalent), and production-grade coding practices
• SQL: Advanced SQL skills needed , including experience with relational data modeling, complex analytical queries (joins, window functions, CTEs), and performance tuning in analytical data platforms (e.g., Spark SQL, T‑SQL, or similar).
• Platform Architecture & ETL:  Required hands-on experience designing and operating end‑to‑end ETL pipelines on an enterprise lakehouse platform, including: Building production-grade pipelines for large-scale transformations with integrated quality enforcement using PySpark and pandas. Implementing batch and/or streaming ingestion using API, file based, Change Data Capture (CDC) patterns. Ability to apply structured data modeling principles to canonical and enriched datasets within a medallion architecture Ability to apply analytics-oriented data modeling principles to data products within a medallion architecture Adhering to data governance practices, including data quality, lineage and auditability, and access control. Monitoring, optimizing, and troubleshooting production data pipelines for performance and reliability.
• Data Engineering Tenure: 5+ years of professional experience in data engineering role. Multi-year track record of delivering production data pipelines at scale required
• Software Engineering Practices:Experience developing and operating production data systems using modern software engineering and SDLC practices.
• Strong, proactive communication skills are a must-have for this position
• Ability to demonstrate technical functionality to both technical and non-technical audiences
• Ownership of work and solution mindset are vital foundations of our work culture

Nice To Haves

• Databricks certifications (Data Engineer Associate/Professional)
• Experience with cloud platforms (AWS or Azure) and their native data services
• Experience with CI/CD for data pipelines and infrastructure-as-code practices preferred
• Familiarity with orchestration tools (Airflow, Prefect, Databricks Workflows)
• Experience with data migration projects or multi-source integration scenarios
• Knowledge of real-time streaming technologies (Kafka, Event Hubs, Kinesis)
• Background in SaaS, ERP, or property management software domains

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT workflows using Python and SQL
• Architect and implement data ingestion patterns for batch, streaming, and hybrid workloads
• Develop and optimize solutions on Databricks big data platforms, leveraging Delta Lake, Spark, and related technologies
• Establish and enforce data quality standards, monitoring, and alerting across the data platform
• Collaborate with data scientists, analysts, and business stakeholders to understand data requirements and deliver reliable data products
• Define and implement medallion architecture (Bronze/Silver/Gold) patterns for data transformation and governance
• Mentor junior engineers and contribute to engineering best practices and documentation

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed