Senior Data Engineer
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Full time
- Experience
- 4+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 4+ years of hands-on data engineering with large-scale distributed data systems and a track record of production ownership (not just development).
- Advanced PySpark: performance tuning, partitioning strategy, and cost-aware cluster sizing on real workloads (EMR or equivalent).
- Strong Python: clean, tested, production-grade code (we use pytest, ruff, mypy, and coverage gates in CI).
- Deep AWS experience: EMR, Glue, Lambda, S3, Athena, Step Functions, EventBridge, IAM, and VPC networking; comfort operating (not just deploying to) these services.
- Advanced SQL: complex analytical queries, query optimization, and data modeling on both a warehouse/lake engine (Athena/Presto) and PostgreSQL.
- Lakehouse experience: hands-on production work with at least one open table format (Apache Hudi strongly preferred; Iceberg or Delta Lake also valued) and medallion-style architecture.
- Data quality mindset: experience implementing validation, quality gates, monitoring, and incident response for production data.
- Infrastructure as Code: Terraform and/or CloudFormation in a CI/CD workflow.
- English and Spanish: professional working proficiency in both (B2+).
- Bachelor’s degree in Computer Science, Systems Engineering, Data Engineering, or equivalent practical experience.
Nice to have
- Real estate, property, or geospatial data experience (county/FIPS-partitioned datasets, address standardization, parcel/permit data).
- Building or operating public/internal data APIs (API Gateway, SQS, DynamoDB caching, SLAs).
- Observability tooling (CloudWatch, Grafana dashboards, structured logging).
- ML-adjacent engineering: feature pipelines, training-data reproducibility, model-serving data paths.
- Modern Python tooling (uv, Poetry) and monorepo/template-driven repo governance.
- Agile/SCRUM experience and a habit of writing documentation others actually use.
Full description
What is 8020REI?
8020REI is a pioneering B2B data and SaaS platform that empowers professional real estate investors to generate consistent leads from Cold Call, SMS, and Direct Mail without spending more. We leverage AI, machine learning, and advanced analytics to identify homeowners likely to sell at a discount, and we use a proven strategy to maximize our clients' ROI. As part of our network, we also operate alongside three sister companies: DMForce, 8020Recruit, and 8020CRM, each contributing specialized services to the real estate sector.
Core Values at 8020REI:
- Find a Better Way: We dig until we understand the real problem, then improve or innovate to solve it. Focused on the 20% that drives the biggest result.
- Have Each Other's Back: We work as a team. We support, step in, and go the extra mile to create a great experience for each other and our clients.
- Honor Your Word: We honor our promises, hold ourselves accountable, and do the right thing even when nobody’s looking.
- Own Your Growth: We're obsessed with personal growth and take pride in the work we deliver. Intrinsically motivated, we hold ourselves to a high standard and never coast.
- Bring Your A-Game: We take care of our recovery, health, and family time, and that’s why we show up focused, energized, and ready to perform at our best.
🎯 Role Overview
We are looking for a Senior Data Engineer to own the design, reliability, and cost-efficiency of our AWS data platform. You will build and optimize the PySpark/EMR pipelines that power our deal-scoring engine (Apollo), our property valuation product (BestEstimate), and our permits and roofing intelligence lines; harden our Hudi-based medallion lakehouse; and operate the data-serving APIs our clients and internal teams depend on.
This is a hands-on senior role with real ownership: you will make architecture decisions, carry the cloud budget for the data platform, enforce our data quality standard, and partner directly with Data Science to turn models into reliable production systems. If you like nationwide-scale data, pragmatic engineering, and seeing your pipelines drive real revenue, this seat is for you.
💡 Key Responsibilities:
- Own Big Data pipelines end to end. Design, build, and optimize PySpark ETL/ELT pipelines on Amazon EMR and AWS Glue that process nationwide, county-partitioned property data (First American, BuildZoom permits, market comps) on daily and monthly cadences.
- Run our lakehouse. Operate and evolve our Bronze → Silver → Gold data lake on S3 with Apache Hudi and the AWS Glue Data Catalog, queried through Athena, including schema contracts, partitioning strategy, compaction, and performance tuning.