DATA ENGINEER

Black Financial Consulting Group; Snowflake (AZ); On-site; USD 120,000 - 160,000; Full time

Job summary

Black Financial Consulting Group is seeking a Data Engineer to design and maintain scalable data pipelines, integrating multiple data sources for analytics and product teams. You will ensure data quality and governance while collaborating with Product, Analytics, and Cloud teams to enable data-driven decisions.

The role emphasizes building ETL/ELT pipelines, optimizing data models, and supporting BI with clean datasets, in a collaborative, Agile environment.

Qualifications

• 6-8 years of experience in data engineering or related roles.
• Strong understanding of data structures, databases, and data modeling.
• Experience building ETL/ELT pipelines in production environments.
• Good problem-solving and analytical skills.
• Experience working in Agile and cross-functional teams.
• Strong communication and documentation abilities.

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT processes.
• Integrate data from multiple sources, including APIs, databases, and third-party systems.
• Develop and optimize data models for analytics and reporting use cases.
• Ensure data quality, integrity, and consistency across systems.
• Support real-time and batch data processing workflows.
• Collaborate with Product and Analytics teams to define data requirements.
• Monitor and troubleshoot data pipeline performance and failures.
• Implement data governance, security, and access controls.
• Support BI and analytics teams with clean and structured datasets.
• Continuously improve data architecture, performance, and scalability.

Skills

Data engineering experience

Data modeling

ETL/ELT pipelines

Python

SQL

Agile cross-functional teams

Data quality

Communication

Tools

Airflow

dbt

Spark

Kafka

PostgreSQL

MySQL

MongoDB

Job description

The Data Engineer will be responsible for building reliable data pipelines, integrating multiple data sources, and ensuring high-quality, accessible, and well-structured data for analytics and product teams. The role works closely with Product, Analytics, Engineering, and Cloud teams to enable data-driven decision-making.

Key Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT processes.
  
• Integrate data from multiple sources, including APIs, databases, and third-party systems.
  
• Develop and optimize data models for analytics and reporting use cases.
  
• Ensure data quality, integrity, and consistency across systems.
  
• Support real-time and batch data processing workflows.
  
• Collaborate with Product and Analytics teams to define data requirements.
  
• Monitor and troubleshoot data pipeline performance and failures.
  
• Implement data governance, security, and access controls.
  
• Support BI and analytics teams with clean and structured datasets.
  
• Continuously improve data architecture, performance, and scalability.
  

Required Qualifications

• 6-8 years of experience in data engineering or related roles.
  
• Strong understanding of data structures, databases, and data modeling.
  
• Experience building ETL/ELT pipelines in production environments.
  
• Good problem-solving and analytical skills.
  
• Experience working in Agile and cross-functional teams.
  
• Strong communication and documentation abilities.
  

Technical Skills

• Programming: Python, SQL (advanced level)
  
• Data Processing: Spark, Kafka, or similar distributed systems (preferred)
  
• Databases: PostgreSQL, MySQL, MongoDB, or equivalent
  
• Data Warehousing: Snowflake, BigQuery, Redshift (preferred)
  
• ETL/ELT Tools: Airflow, dbt, or similar
  
• BI Tools: Tableau, Power BI, or similar (supporting role) Tableau