Data Engineer
Description
Overview
Black Canyon Consulting (BCC) is searching for a Data Engineer to support the design, development, and maintenance of data infrastructure that enables artificial intelligence, machine learning, and analytical workloads. The Data Engineer will help ensure that data is reliable, accessible, scalable, and operationally ready throughout the full lifecycle from ingestion through deployment.
Job Description
The Data Engineer will design, implement, maintain, and optimize data pipelines, APIs, data transformation workflows, and supporting infrastructure. This position will work with databases, data lakes, data warehouses, feature stores, and other data platforms to ensure information can be efficiently ingested, transformed, accessed, and used by analytical and AI-enabled systems.
The Data Engineer will also develop and maintain ETL/ELT processes, feature engineering workflows, and service layers that expose data or model endpoints to downstream systems and applications.
Duties and Responsibilities
- Develop and maintain data ingestion and transformation pipelines using Python and SQL.
- Implement bronze, silver, and gold data processing patterns using DuckDB and Apache Iceberg.
- Build reusable, metadata-driven capabilities for ingesting data from databases, APIs, files, SaaS platforms, CDC, and event-driven sources.
- Develop configuration-driven source onboarding and source-to-canonical data mappings.
- Transform heterogeneous source data into standardized and governed data models while maintaining source provenance and traceability.
- Implement agentic and AI-enabled workflows to support source profiling, schema analysis, data mapping, pipeline generation, testing, troubleshooting, reconciliation, and data quality.
- Develop automated data validation, reconciliation, testing, monitoring, and error-handling capabilities.
- Support incremental processing, schema evolution, backfills, and historical data migration.
- Integrate structured data with related document and geospatial datasets where required.
- Work with the Data Architect and Lead Data Engineer to implement common engineering standards and reusable platform patterns.
- Participate in code reviews, automated testing, CI/CD, technical documentation, and operational support.
Requirements
- 4+ years of relevant data engineering or software engineering experience.
- Strong hands-on experience with Python, SQL, DuckDB, and Apache Iceberg.
- Experience developing production ETL/ELT pipelines across databases, APIs, files, and semi-structured data sources.
- Experience implementing bronze/silver/gold or comparable layered data architectures.
- Experience designing reusable, metadata-driven ingestion and transformation pipelines.
- Experience with AWS data services, particularly Amazon S3 and AWS Glue.
- Experience with data modeling, source-to-target mappings, data quality, reconciliation, and schema evolution.
- Experience developing or implementing agentic or AI-enabled data engineering workflows, including the use of AI agents or LLMs to assist with data engineering tasks.
- Experience with Git-based development, automated testing, and CI/CD.
Bonus Skills
- Experience with agentic frameworks such as LangChain, LangGraph, or similar orchestration frameworks.
- Experience with Kafka, Amazon MSK, or CDC technologies.
- Experience integrating Salesforce, ServiceNow, Microsoft Dataverse, or similar enterprise platforms.
- Experience with OpenSearch, vector stores, or document-processing pipelines.
- Experience with GeoParquet, PostGIS, or geospatial datasets.
- Experience working in the U.S. Federal Government space.
- Experience with permitting, regulatory, land management, environmental, energy, or natural-resource datasets.
Benefits and Salary
We attract the best people in the business with our competitive benefits package that includes medical, dental and vision coverage, 401k plan with employer contribution, paid holidays, vacation, and tuition reimbursement.
If you enjoy being a part of a high performing, professional service and technology focused organization, please apply today!
Skills
- Agentic AI
- AI
- API
- AWS
- Aws Glue
- CI/CD
- Data Engineering
- Data Ingestion
- Data Lake
- Data Modeling
- Data Pipelines
- Data Quality
- Dataverse
- ELT
- ETL
- Event Driven Architecture
- Feature Engineering
- Git
- Iceberg
- Kafka
- LangChain
- LangGraph
- LLM
- Machine Learning
- OpenSearch
- Python
- S3
- SaaS
- Salesforce
- ServiceNow
- SQL
- Test Automation
As published by greenhouse · 7 questions · 4 written answers
Basics
First Name, Last Name, Email, Phone, Resume/CV, Cover Letter, Location
Short answers (2)
- What are your salary requirements?
- How many years of relevant professional experience do you have in data engineering or a closely related field?
Pick from a list (1)
- Will you now, or in the future, require visa sponsorship? This includes if you are on a STEM OPT, J-1, F-1 visa currently.
Written answers (4)
- Briefly describe one data pipeline you personally designed or significantly contributed to. What data was being processed, what technologies did you use, and what was your role?
- Describe a situation where a data pipeline had a reliability, performance, or data-quality problem. What was the issue, how did you identify it, and what did you do to resolve it?
- Which programming or query languages have you used professionally for data engineering?
- How have you developed or maintained APIs or service layers used to expose data, analytical results, or model endpoints?
