Data Engineer
Our Story
Over the past several years, Able has grown immeasurably. We’ve also grown in the type of company that we are:
Chapter 1: We were founded in 2013 as a product and engineering hub for a portfolio of early-stage start-ups. We grew up as an in-house/external hybrid shared services model. That allowed us to hone our skills and establish our operational and cultural foundation.
Chapter 2: In 2019 we began to expand our vision. We began to grow outside of our inset partner base. We had good initial success meeting new partners, kicking off new relationships, and delivering high-value work.
Chapter 3: In 2023, we moved into the next phase of a new chapter, an expansion of the ambition of Chapter 2. Our strategy for growth centers around two audiences:
- Venture Capital: VC firms are looking for trusted product and technology solutions to distribute seamlessly across their portfolios at scale.
- Private Equity: PE firms are looking for trusted solutions that can catalyze growth for their portfolio companies at scale.
Chapter 3a: We are now in the next phase of Chapter 3, aligned to our mission and vision, and accelerated by the powers of applied AI. We believe that AI will be a powerful force in the end-to-end software development lifecycle. Specifically we are creating practices that – coupled with our world class talent – can deliver software significantly faster than legacy techniques. The result is increased value for our partners, who can dramatically increase the capacity of their product organizations.
About the Role
Supporting the Director of Engineering and the broader Engineering team, this Data Engineer role will work cross-functionally with teams across Able while aligning closely with the Engineering discipline. This role will partner directly with a specific client and collaborate across Product, Design, and Engineering to deliver robust and scalable data solutions that meet critical business needs.
Day-to-Day Responsibilities
Strategic Architecture Leadership
- Shape large-scale data architecture vision and roadmap across client engagements
- Establish governance, security frameworks, and regulatory compliance standards
- Lead strategy around platform selection, integration, and scaling
- Guide organizations in adopting data lakehouse and federated data models
Client/Partner Value Creation
- Lead technical discovery sessions to understand client needs
- Translate complex architectures into clear, actionable value for stakeholders
- Build trusted advisor relationships and guide strategic decisions
- Align architecture recommendations with business growth and goals
Technical Architecture & Implementation
- Design and implement modern data lakehouse architectures with Delta Lake and Databricks
- Build and manage ETL/ELT pipelines at scale using Spark (PySpark preferred)
- Leverage Delta Live Tables, Unity Catalog, and schema evolution features
- Optimize storage and queries on cloud object storage (e.g., AWS S3, Azure Data Lake)
- Integrate with cloud-native services like AWS Glue, GCP Dataflow, and Azure Synapse Analytics
- Implement data quality monitoring, lineage tracking, and schema versioning
- Build scalable pipelines with tools like Apache Airflow, Step Functions, and Cloud Composer
Business Impact & Solution Design
- Develop cost-optimized, scalable, and compliant data solutions
- Design POCs and pilots to validate technical approaches
- Translate business requirements into production-ready data systems
- Define and track success metrics for platform and pipeline initiatives
What We’re Looking For
The ideal candidate will have:
- 10+ years of data engineering experience with enterprise-scale systems
- Expertise in Apache Spark and Delta Lake, including ACID transactions, time travel, Z-ordering, and compaction
- Deep knowledge of Databricks (Jobs, Clusters, Workspaces, Delta Live Tables, Unity Catalog)
- Experience building scalable ETL/ELT pipelines using tools like Airflow, Glue, Dataflow, or ADF
- Advanced SQL for data modeling and transformation
- Strong programming skills in Python (or Scala)
- Hands-on experience with data formats such as Parquet, Avro, and JSON
- Familiarity with schema evolution, versioning, and backfilling strategies
- Working knowledge of at least one major cloud platform:
- AWS (S3, Athena, Redshift, Glue Catalog, Step Functions)
- GCP (BigQuery, Cloud Storage, Dataflow, Pub/Sub) – nice to have
- Azure (Synapse, Data Factory, Azure Databricks) – nice to have
- Experience designing data architectures with real-time or streaming data (Kafka, Kinesis)
- Consulting or client-facing experience with strong communication and leadership skills
- Experience with data mesh architectures and domain-driven data design
- Knowledge of metadata management, data cataloging, and lineage tracking tools
- Familiarity with healthcare standards (e.g., HL7, FHIR, DICOM) is a plus
- Awareness of international data privacy regulations and compliant system design
Nice to have:
- Master's degree in Computer Science, Data Engineering, or related field
- ML Ops experience or integrating machine learning models into data pipelines
- Relevant certifications in cloud platforms or data engineering
This is a contract position. This position is 100% remote within LatAm. Strong verbal and written communication skills in English are a requirement.
This contract period is for 4-6 months, starting in August 2025. Candidates are expected to work 40 hours per week during this contract period, and be available during normal business hours as-needed on this project.
A contract extension is possible, pending our client partnership and individual performance. Those candidates interested in a future long term contract position would be considered an asset.
Able's Values
- Put People First: We're caring, open, and encouraging. We respect the richness that we each bring into our work.
- Imagine Better: We are optimistic in our outlook, as well as creative and proactive to deliver the highest quality.
- Expect Excellence: We commit to each other to always strive to be our best.
- Simplify to Solve: We create better outcomes by reducing complexity.
- We are all Builders: We are motivated and empowered to help build Able, and our partner's businesses.
- One Able. Many Voices: Our unity is our strength. Our diversity is our energy.
Let’s build together.
