[Hiring] Data Pipeline & Analytics Engineering Consultant @24-MAG

Role Description

We are sharing a specialised part-time consulting opportunity for professionals experienced in data engineering, analytics engineering, ETL/ELT workflows, pipeline orchestration, data quality testing, warehouse design, and structured technical documentation processes. This role supports current and upcoming remote consulting opportunities focused on structured data pipeline review, analytics engineering workflow analysis, orchestration assessment, data quality validation, warehouse documentation, and high-quality project execution. Selected professionals will apply their data engineering expertise to review realistic pipeline scenarios, evaluate technical requirements, prepare structured written outputs, and support accurate, evidence-based data workflow tasks.

Key Responsibilities

• Pipeline Development & ETL/ELT Review
  • Review data engineering scenarios involving ETL/ELT pipelines, dbt models, incremental logic, watermark behavior, transformations, and output tables.
  • Evaluate pipeline outputs against defined data contracts, expected table structures, source materials, and transformation requirements.
  • Support structured review of SQL models, dbt projects, pipeline documentation, transformation logic, and data processing workflows.
  • Identify missing logic, incorrect transformations, schema issues, and expected pipeline outcomes.
• Orchestration, Testing & Data Quality
  • Review orchestration scenarios involving Airflow, Dagster, Prefect, scheduled jobs, DAG dependencies, retries, and workflow execution.
  • Evaluate data quality tests against known pass/fail cases, validation rules, test suites, and documented expectations.
  • Support structured review of data quality checks, pipeline test cases, orchestration documentation, and monitoring workflows.
  • Prepare clear written explanations for data engineering decisions based on source materials and verifiable criteria.
• Warehouse Design & Data Contracts
  • Review warehouse design scenarios involving schemas, data models, performance targets, query-time budgets, partitioning, clustering, and storage design.
  • Evaluate schema designs against defined contracts, downstream requirements, performance expectations, and documented constraints.
  • Support structured review of data contracts, schema documentation, warehouse models, and analytics engineering artifacts.
  • Maintain accuracy, consistency, and professional judgment across submitted work.

Qualifications

• 3+ years of experience in data engineering, analytics engineering, data platform engineering, BI engineering, warehouse engineering, or related technical roles.
• Experience with one or more areas such as dbt model development, ETL/ELT pipelines, orchestration, data quality testing, warehouse design, schema documentation, incremental models, or data contracts.
• Familiarity with tools and platforms such as dbt, Airflow, Dagster, Prefect, Snowflake, BigQuery, Redshift, Databricks, Spark, SQL, Python, or similar data engineering systems.
• Comfort reading and preparing data engineering artifacts such as dbt models, DAGs, schema docs, data contracts, test suites, pipeline documentation, and warehouse diagrams.
• Strong written communication skills and ability to explain data engineering reasoning clearly.
• Ability to follow structured instructions and produce evidence-based work.

Educational Background

• Bachelor's or master's degree in computer science, data engineering, information systems, software engineering, statistics, mathematics, or a related technical field is helpful.
• Equivalent practical experience in data engineering, analytics engineering, data platform work, pipeline development, or warehouse design is also highly relevant.

Nice to Have

• Experience with dbt model development, data contracts, incremental models, data lineage, orchestration frameworks, or modern data stack workflows.
• Familiarity with Snowflake, BigQuery, Redshift, Databricks, Spark, SQL optimization, Python-based pipelines, or cloud data platforms.
• Experience preparing or reviewing DAGs, schema documentation, data quality tests, transformation logic, warehouse models, or pipeline runbooks.
• Familiarity with CI/CD for data pipelines, data observability, testing frameworks, or performance tuning.
• Strong attention to detail in code-heavy, data-heavy, and documentation-based technical environments.

Why This Opportunity

• Apply data engineering and analytics engineering expertise to structured remote project work.
• Contribute to high-quality pipeline review, data quality assessment, orchestration analysis, and warehouse documentation workflows.
• Work on flexible, project-based assignments aligned with your professional background.
• Use your data engineering judgment in a focused, detail-oriented consulting environment.
• Remote structure with competitive hourly compensation.

Contract Details

• Independent contractor role.
• Fully remote with flexible scheduling.
• Part-time commitment depending on project availability.
• Competitive rates between $95–$135 per hour depending on expertise.
• Weekly payments via Stripe or Wise.
• Projects may be extended, shortened, or adjusted depending on scope and performance.
• Work will not involve access to confidential or proprietary information from any employer, client, or institution.

About the Platform

This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.

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