AWS Data Engineer (Senior)

Neura Market

Northern (KY)

Hybrid

USD 120,000 - 180,000

Full time

9 days ago

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Job summary

Mactores is seeking a senior Data Platform Engineer to consolidate and migrate customer data infrastructure on AWS. You will own data models, pipelines, and cutover decisions, building with PySpark and SQL on EMR/Glue and orchestrating with Airflow.

You’ll work directly with customers and cross-functional teams to design scalable solutions that perform under real load. You will lead architecture decisions, ensure production readiness, and stay ahead of evolving AWS data technologies.

Qualifications

  • Bachelor's degree in Computer Science, Engineering, or a related field.

Responsibilities

  • 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 customer and internal 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 — customers sign off on what we ship.
  • Track new AWS data technologies and judge their impact on the systems we run.

Skills

PySpark
SQL
Problem-solving
Communication
Teamwork
Independent work

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Amazon EMR
Amazon Glue
Amazon Redshift
Snowflake
Athena
Presto
Airflow

Job description

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 role in our Data Platform Modernization pillar: consolidating and migrating customer data infrastructure on AWS in weeks, not quarters, at meaningfully lower engagement cost than traditional data consulting. 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 own what agents can't: target architecture, data model decisions, pipeline design under real constraints, and the calls that make a cutover safe. You'll build with PySpark and SQL on EMR and Glue, model for Redshift, Snowflake, Athena, and Presto, orchestrate with Airflow and your work will reach production, not a slide deck.

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 customer and internal 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 — customers sign off on what we ship.
  • 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. Senior engineers embed with the customer's team, own outcomes from discovery through production, and carry the delivery commitment personally fixed dates, with Mactores absorbing overage cost for delays inside our control. Aedeon absorbs scale; you absorb judgment. That means less of your week goes to inventory spreadsheets and manual validation, and more goes to architecture, data modeling, and cutover strategy. The culture is casual and steers clear of rigid corporate habits. We measure ourselves by what ships.

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.

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