Title
ETL Developer
Quick Summary
DeltaBridge Data is hiring an ETL Developer to design, build, and operate reliable data pipelines that power analytics and machine learning across multiple business lines. You will own ingestion, transformation, and loading workflows for both batch and streaming use cases, ensuring data is accurate, timely, and cost-efficient. We welcome strong graduates and early-career engineers with practical projects in SQL, Python, and orchestration.
Project Category or Industry
Data engineering for SaaS, analytics, and digital products.
Type
Full-time employment.
Experience Level
Entry to mid-level with structured mentorship; experienced applicants are also welcome.
Duration
Permanent role.
Location
Remote-first with optional collaboration hubs in Denver and Kraków. Maintain at least four hours of overlap with teams operating between UTC−7 and UTC+2.
Salary
USD 88,000–128,000 base depending on location and experience, plus benefits and an annual performance bonus.
Payment Mode
Monthly payroll where supported; compliant contractor arrangements available in select countries.
Hiring Company Name
DeltaBridge Data
Required Skills or Tools
Strong SQL and Python, practical experience with orchestration and transformation tooling, and comfort working in a cloud environment. Familiarity with distributed processing, data modeling, quality validation, and observability is important to succeed quickly.
Project Description
DeltaBridge Data builds modern data platforms for analytics and product teams. As an ETL Developer, you will turn business requirements into robust pipelines and curated datasets. The role spans source discovery and contracts, schema design, transformation logic, and monitoring so downstream users can trust the data for dashboards, experimentation, and model features.
Core Responsibilities and Expected Deliverables
Translate requirements into scalable ingestion and transformation workflows for batch and streaming sources.
Model clean, well-documented tables optimized for consumption in a lakehouse and warehouse.
Implement data quality checks, lineage, and alerts; define SLAs for freshness, completeness, and accuracy.
Optimize pipeline performance and cost with partitioning, incremental loads, and sensible scheduling.
Deliver reproducible code, automated tests, and clear runbooks; participate in code reviews and on-call rotations.
Partner with analytics, data science, and platform teams to prioritize roadmaps and enable self-service.
Required Experience and Preferred Qualifications
Proficiency in SQL and Python with solid engineering discipline (version control, testing, CI/CD).
Hands-on experience with at least one orchestrator (Airflow, Dagster, or Prefect) and a transformation framework such as dbt.
Working knowledge of a warehouse (Snowflake, BigQuery, or Redshift) and lakehouse formats (Delta Lake, Iceberg, or Hudi).
Familiarity with distributed processing (Spark or Flink) and event streaming (Kafka or Kinesis).
Preferred: Great Expectations for validation, OpenLineage or DataHub for lineage, Terraform for infrastructure as code, and Kubernetes for runtime management.
Evidence of impact via internships, open-source contributions, coursework, or shipped pipelines will be valued.
Tools or Platforms to Be Used
Orchestration and transformations: Airflow or Dagster, dbt.
Processing and storage: Spark, Kafka, S3/GCS, Delta Lake/Iceberg/Hudi.
Warehousing and queries: Snowflake, BigQuery, or Redshift; strong SQL for optimization.
Observability and governance: Great Expectations, OpenLineage/Marquez, DataHub, Prometheus, Grafana.
Infrastructure: Terraform, Docker, GitHub Actions; primary cloud on AWS or GCP.
Language Requirement
Professional English is required. Additional languages are helpful for cross-regional collaboration.
Communication Style
Written-first collaboration with design docs and pull requests in GitHub; Slack for daily coordination; Zoom for stand-ups, reviews, and incident retrospectives. Clear documentation is expected for all changes.
Time Commitment or Working Window
Standard 40 hours per week with flexible scheduling. Maintain a predictable daily block that overlaps at least four hours with the core team between 09:00 and 17:00 in your local time.
Payment Terms
Salary is paid monthly via payroll. For contractors, invoices are processed on net-30 terms upon acceptance of deliverables and timesheets.
Evaluation Criteria
Portfolio or code samples demonstrating pipeline reliability, data modeling clarity, and operational discipline.
Practical exercise building an incremental ETL pipeline with validation and lineage.
Technical interview covering partitioning, scheduling, performance, and cost governance.
Final conversation on collaboration, product sense, and communication.
References may be requested.
Other Requirements
New hires sign a confidentiality agreement and comply with security and data-handling policies. Light time-tracking may be used for distributed coordination. Occasional on-call for data incidents is shared across the team.
About DeltaBridge Data
DeltaBridge Data is a privately held data engineering firm that delivers modern platforms and analytics foundations for clients in commerce, media, and financial services. Headquartered in Denver with a distributed workforce across North America and Europe, we pair rigorous engineering with practical operations to provide trustworthy, cost-effective data systems. Learn more at https://www.deltabridgedata.com and reach our hiring team at careers@deltabridgedata.com.