About this role.
This senior freelance Data Engineer role delivers AWS data-platform modernization projects for customers whose data programs have stalled. The engineer will build production PySpark and SQL pipelines using EMR or Glue, model and query data across Redshift, Snowflake, Athena, and Presto, and orchestrate workloads with Airflow. The work emphasizes troubleshooting, performance optimization, cutover readiness, and production outcomes on committed delivery timelines. It is a hands-on, remote contract engagement requiring independent ownership and close coordination with delivery teams and customer stakeholders.
Role DNA
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Job Complexity
4/5Pace & Pressure
5/5Autonomy Level
5/5Communication Load
4/5Salary analysis
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Core skills
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Sample interview questions
I would explain the source systems, ingestion and transformation design, partitioning strategy, data-quality controls, monitoring, and how I tuned Spark execution for reliability and cost. I would also quantify the outcome, such as reduced processing time, improved freshness, or fewer pipeline failures.
I would begin with workload discovery, schema and dependency mapping, data profiling, and target-platform design. I would then migrate incrementally, validate data and query results through parallel runs, optimize storage and query patterns, and plan a reversible cutover with clear acceptance criteria.
I use idempotent tasks, explicit dependencies, retries with sensible backoff, alerting, SLAs, and parameterized configurations. I also design for backfills, isolate reusable operators, manage secrets securely, and ensure failed runs can be diagnosed and recovered without corrupting downstream data.
I first inspect job stages, executor metrics, skew, shuffle volume, partition sizing, and input-file layout. Based on findings, I may adjust partitioning, reduce shuffles, broadcast appropriate joins, address skew, tune resource settings, and improve storage formats such as Parquet while validating performance against representative workloads.
I translate choices into delivery impact, risk, cost, timeline, and measurable business outcomes rather than focusing only on implementation details. I document assumptions, trade-offs, validation results, and cutover plans in concise language, then use regular checkpoints to keep stakeholders aligned.
Mactores is the agent-native AWS modernization firm. Most modernization work doesn’t ship, it stalls in pilots, slips a year, or lands at three times the budget. We exist to ship it: production systems running, legacy retired, outcomes measured. Our delivery is built on Aedeon, the agent platform built by Mactores’ founders’ sister company, which absorbs the repetitive 60–70% of engagement work, discovery, dependency mapping, validation, test generation, that traditional consulting bills human hours against. Forward-deployed engineers own the rest: architecture, judgment, and cutover, on dates we commit to in the contract.
This is a senior freelance role in our Data Platform Modernization pillar: consolidating and migrating customer data infrastructure on AWS in weeks, not quarters. Customers come to us after a data program has stalled — pipelines nobody trusts, warehouses nobody runs new workloads on, a modernization that produced diagrams instead of production systems.
Aedeon handles automated source discovery, schema mapping, lineage extraction, and parallel-run validation. You take the work that needs a senior engineer’s judgment: pipeline builds on EMR and Glue, data models for Redshift, Snowflake, Athena, and Presto, Airflow orchestration, and the troubleshooting that gets a system stable enough to cut over. Freelance here means real delivery work on real engagements — not staff augmentation into someone else’s backlog.
What you will do?
- Build and maintain data pipelines on Amazon EMR or Amazon Glue that run in production.
- Design data models and end-user querying on Amazon Redshift or Snowflake, Amazon Athena, and Presto.
- Build and maintain pipeline orchestration with Airflow.
- Work with other teams to understand data needs and design the solutions that meet them.
- Troubleshoot and optimize pipelines and data models until they hold up under real load.
- Write and maintain PySpark and SQL scripts to extract, transform, and load data.
- Document and communicate technical decisions to technical and non-technical audiences.
- Track new AWS data technologies and judge their impact on the systems we run.
What are we looking for?
- Bachelor’s degree in Computer Science, Engineering, or a related field.
- 3+ years of experience working with PySpark and SQL.
- 2+ years of experience building and maintaining data pipelines using Amazon EMR or Amazon Glue.
- 2+ years of experience with data modeling and end-user querying using Amazon Redshift or Snowflake, Amazon Athena, and Presto.
- 1+ years of experience building and maintaining pipeline orchestration using Airflow.
- Strong problem-solving and troubleshooting skills.
- Excellent communication and collaboration skills.
- Ability to work independently and within a team environment.
You are preferred if you have
- AWS Data Analytics Specialty Certification
- Experience with Agile development methodology
How we work?
We run a forward-deployed model: engineers embed with delivery teams, own their piece of the outcome, and ship against committed dates. This is a remote freelance engagement, so we’ll be straight about the shape: you work project-by-project inside that model, with Aedeon absorbing the repetitive layer so your billed time goes to engineering judgment, not manual validation. You’ll work independently, coordinate closely with the engagement team, and your output lands in production systems that customers sign off on.
Compensation
Additional Information
Life at Mactores
We care about creating a culture that makes a real difference in the lives of every Mactorian. Our 10 Core Leadership Principles that honor Decision-making, Leadership, Collaboration, and Curiosity drive how we work.
1. Be one step ahead
2. Deliver the best
3. Be bold
4. Pay attention to the detail
5. Enjoy the challenge
6. Be curious and take action
7. Take leadership
8. Own it
9. Deliver value
10. Be collaborative
We would like you to read more details about the work culture on https://mactores.com/careers
The Path to Joining the Mactores Team
At Mactores, our recruitment process is structured around three distinct stages:
Pre-Employment Assessment:
A series of evaluations of your technical proficiency and suitability for the role.
Managerial Interview: The hiring manager engages with you in multiple discussions, 30 minutes to an hour each, covering technical skills, hands-on experience, leadership potential, and communication.
HR Discussion: During this 30-minute session, you’ll have the opportunity to discuss the offer and next steps with a member of the HR team.
Mactores provides equal opportunities in all employment practices. We don’t discriminate based on race, religion, gender, national origin, age, disability, marital status, military status, genetic information, or any other category protected by federal, state, and local laws. This applies to every part of the employment relationship, recruitment, compensation, promotions, transfers, disciplinary action, layoff, training, and social and recreational programs.
Note: Please answer as many questions as possible with this application to accelerate the hiring process.
Annual salary information is not provided for this position. Explore salary ranges for similar roles in our Salary Directory ›
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