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Black Financial Consult

DATA ENGINEER

Posted 21 days ago
Worldwide
$750 - $1500 per year
5-10 years experience
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AI Summary

The Data Engineer will design, build, and maintain scalable data pipelines and ETL/ELT processes to integrate multiple data sources. They will also ensure data quality and collaborate with cross-functional teams to support analytics and data-driven decision-making.

This is a remote position.

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)
  • Cloud Platforms: Amazon Web Services / Azure / GCP
  • ETL/ELT Tools: Airflow, dbt, or similar
  • Version Control: Git / GitHub / GitLab
  • BI Tools: Tableau, Power BI, or similar (supporting role) Tableau

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