Remote | Data Pipeline & Analytics Engineering Consultant — $95–$135/hour24-MAG • New York, New York, United States
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Remote | Data Pipeline & Analytics Engineering Consultant — $95–$135/hour
24-MAG
- New York, New York, United States
- New York, New York, United States
À propos
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 Professionals in this role may contribute to:
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
Ideal Profile
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
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Compétences linguistiques
- English
Avis aux utilisateurs
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