Remote | Data Pipeline & Analytics Engineering Consultant — $95–$135/hour
24-MAG · New York, NY
- Hybrid
- Contract
- $125,000 / year
- New York, NY
Job highlights
- Consult on data pipelines and analytics workflows.
- Review ETL/ELT, dbt models, and orchestration.
- Validate data quality and warehouse designs.
- Remote, part-time consulting with flexible hours.
- Earn $95-$135 hourly based on expertise.
About the role
Data Pipeline & Analytics Engineering Consultant
24-MAG is seeking experienced professionals for a part-time consulting opportunity focused on data engineering and analytics engineering. This remote role involves reviewing data pipelines, assessing analytics engineering workflows, evaluating orchestration, validating data quality, documenting warehouses, and executing high-quality projects. You will leverage your expertise to analyze realistic pipeline scenarios, evaluate technical requirements, prepare written outputs, and perform evidence-based data workflow tasks.
Key Responsibilities
- Pipeline Development & ETL/ELT Review: Examine ETL/ELT pipelines, dbt models, incremental logic, watermark behavior, transformations, and output tables.
- Evaluate pipeline outputs against data contracts, 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 including Airflow, Dagster, Prefect, scheduled jobs, DAG dependencies, retries, and workflow execution.
- Evaluate data quality tests against 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 dbt model development, ETL/ELT pipelines, orchestration, data quality testing, warehouse design, schema documentation, incremental models, or data contracts.
- Familiarity with tools 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 like 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
- A 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. By submitting this application, you acknowledge that your information may be processed by 24-MAG LLC for recruitment and opportunity matching in accordance with our Privacy Policy: https://www.24-mag.com/privacy-policy
Key skills/competency
- Data Engineering
- Analytics Engineering
- ETL/ELT
- dbt
- Data Quality
- Orchestration
- SQL
- Python
- Snowflake
- BigQuery
Skills & topics
- Data Engineering
- Analytics Engineering
- ETL
- ELT
- dbt
- Data Pipeline
- Orchestration
- Data Quality
- SQL
- Python
- Consultant
- Remote
- Part-time
- Contractor
- Snowflake
- BigQuery
- Airflow
- Dagster
- Prefect
- Warehouse Design
How to get hired
- Tailor your resume: Highlight experience in data engineering, analytics engineering, ETL/ELT, dbt, and orchestration.
- Showcase technical skills: Emphasize proficiency with SQL, Python, Snowflake, BigQuery, Airflow, or Dagster.
- Demonstrate communication: Provide examples of your ability to write clear, evidence-based technical documentation.
- Understand the role: Focus on your ability to critically review and assess data workflows and designs.
- Follow instructions carefully: Ensure your application and any submitted work adhere strictly to provided guidelines.
Technical preparation
Practice SQL query optimization.,Build sample dbt models.,Create small Airflow DAGs.,Document a mock data warehouse.
Behavioral questions
Describe a complex pipeline review.,Explain a data quality issue found.,How do you handle ambiguous requirements?,Detail your documentation process.
Frequently asked questions
- How does the application process work for a Data Pipeline & Analytics Engineering Consultant at 24-MAG?
- To apply for the Data Pipeline & Analytics Engineering Consultant role at 24-MAG, you'll typically submit your information through their platform. They then use this to match you with suitable remote consulting opportunities. Ensure your resume clearly highlights your expertise in data engineering, analytics engineering, ETL/ELT processes, dbt, orchestration, and data quality.
- What kind of projects can I expect as a Data Pipeline & Analytics Engineering Consultant for 24-MAG?
- As a Data Pipeline & Analytics Engineering Consultant with 24-MAG, you can expect project-based work focusing on reviewing existing data pipelines, assessing analytics engineering workflows, evaluating orchestration tools like Airflow or Dagster, validating data quality, and reviewing warehouse designs and data contracts. These are typically remote, part-time assignments.
- Is this Data Pipeline & Analytics Engineering Consultant role at 24-MAG a full-time or part-time position?
- The Data Pipeline & Analytics Engineering Consultant role with 24-MAG is a part-time, independent contractor position. The commitment varies depending on project availability and scope. This offers flexibility for professionals looking to supplement their income or engage in focused, project-based work.
- What are the typical technical skills required for the Data Pipeline & Analytics Engineering Consultant role at 24-MAG?
- Key technical skills for the Data Pipeline & Analytics Engineering Consultant role include strong experience in data engineering, analytics engineering, ETL/ELT, dbt, orchestration (Airflow, Dagster, Prefect), data quality testing, and warehouse design. Familiarity with SQL, Python, and cloud data platforms like Snowflake or BigQuery is also essential.
- How is compensation handled for the Data Pipeline & Analytics Engineering Consultant role at 24-MAG?
- Compensation for the Data Pipeline & Analytics Engineering Consultant role at 24-MAG is competitive and paid hourly, ranging from $95 to $135, depending on your expertise and the specific project requirements. Payments are typically made weekly via Stripe or Wise.
- Can I work remotely as a Data Pipeline & Analytics Engineering Consultant for 24-MAG?
- Yes, this Data Pipeline & Analytics Engineering Consultant opportunity with 24-MAG is fully remote. This allows consultants to work from anywhere, offering significant flexibility in terms of location and scheduling, aligning with project demands.