Strategic Overview
AWS Data Engineer (Associate) at Mactores is a data opportunity centered on the specialist responsibilities and outcomes described in the employer's listing.
The published role emphasizes work such as Write efficient PySpark and Amazon Glue code that ships to production. Write SQL in Amazon Athena and Amazon Redshift.
The role is listed for United States with remote working arrangement, giving candidates the practical context needed to assess fit before applying. Relevant signals in the listing include Data Science & Analytics, Senior.
Key information at a glance
About This Role
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,…
This role sits in our Data Platform Modernization pillar: consolidating and migrating customer data infrastructure on AWS in weeks, not quarters. Customers come to us with pipelines nobody trusts, metrics nobody agrees on, and warehouses that stall every new business question. You'll build the data products that fix that — working with business leads, analysts, and data scientists to understand the domain, then…
Because Aedeon handles the repetitive layer source discovery, schema mapping, validation harnesses — you won't spend your early career grinding through spreadsheet audits. You'll spend it writing code that reaches production and learning judgment from engineers who own cutovers. Data quality isn't a checkbox here; it's the product.
Key Responsibilities & Objectives
- Write efficient PySpark and Amazon Glue code that ships to production.
- Write SQL in Amazon Athena and Amazon Redshift.
- Pick up new technologies and techniques and put them to work on real business problems.
- Work across engineering and business teams to build data products and services people actually use.
Required Qualifications & Candidate Blueprint
- 1 to 3 years of experience in Apache Spark, PySpark, and Amazon Glue.
- 2+ years of experience writing ETL jobs using PySpark and SparkSQL.
- 2+ years of experience with SQL queries and stored procedures.
Preferred Qualifications
- Prior experience in working on AWS EMR, Apache Airflow
- Certifications AWS Certified Big Data – Specialty OR Cloudera Certified Big Data Engineer OR Hortonworks Certified Big Data Engineer
- Understanding of DataOps Engineering
Salary & Benefits
The available source data does not publish a numerical salary range for this opening. We do not estimate or substitute third-party figures.
Full Job Description
The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.
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 role sits in our Data Platform Modernization pillar: consolidating and migrating customer data infrastructure on AWS in weeks, not quarters. Customers come to us with pipelines nobody trusts, metrics nobody agrees on, and warehouses that stall every new business question. You'll build the data products that fix that — working with business leads, analysts, and data scientists to understand the domain, then shipping pipelines and models that hold up in production.
Because Aedeon handles the repetitive layer source discovery, schema mapping, validation harnesses — you won't spend your early career grinding through spreadsheet audits. You'll spend it writing code that reaches production and learning judgment from engineers who own cutovers. Data quality isn't a checkbox here; it's the product.
What you will do?
- Write efficient PySpark and Amazon Glue code that ships to production.
- Write SQL in Amazon Athena and Amazon Redshift.
- Pick up new technologies and techniques and put them to work on real business problems.
- Work across engineering and business teams to build data products and services people actually use.
- Deliver projects with the team and land customer updates on time.
What are we looking for?
- 1 to 3 years of experience in Apache Spark, PySpark, and Amazon Glue.
- 2+ years of experience writing ETL jobs using PySpark and SparkSQL.
- 2+ years of experience with SQL queries and stored procedures.
- Deep understanding of the Dataframe API and the transformation functions supported by Spark 2.7+.
You will be preferred if you have
- Prior experience in working on AWS EMR, Apache Airflow
- Certifications AWS Certified Big Data – Specialty OR Cloudera Certified Big Data Engineer OR Hortonworks Certified Big Data Engineer
- Understanding of DataOps Engineering
How we work?
We run a forward-deployed model. Engineers embed with the customer's team, own outcomes from discovery through production, and carry the delivery commitment personally. Aedeon absorbs scale; engineers absorb judgment; the contract absorbs risk. As an associate, you'll work inside that model from day one shipping alongside senior engineers rather than watching from a bench. The culture is casual and steers clear of rigid corporate habits. We care about what ships, and we let you be yourself while you ship it.
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
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.
Editor’s Market Perspective (Our Custom Analysis)
Why This Position Matters
This data opening is a useful opportunity for candidates whose experience matches Data Science & Analytics, Senior. Its strongest career signal is the scope of the work itself — particularly Write efficient PySpark and Amazon Glue code that ships to production. — rather than a generic title alone.
Resume & Application Strategy
For the application, mirror the employer's language where it truthfully matches your background: foreground Data Science & Analytics, Senior, quantify outcomes from comparable work, and place the most relevant experience near the top of the resume. If the listing specifies tools, platforms, leadership scope, or domain experience, use those exact terms in context instead of presenting an unrelated keyword list.
We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.