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Data Engineer

Ace Technologies, Inc.United States🇺🇸United StatesPosted Oct 2, 2026

Why This Role Stands Out

This remote Data Engineer role at Ace Technologies offers an exciting opportunity to build scalable data pipelines and contribute to a renowned tech company, with excellent potential for career growth. If you have a strong background in AWS data platforms and ETL development, you'll thrive in this position and gain valuable experience. Apply today to leverage your skills and advance your career!

Quick Overview

Seniority
Mid Senior
Work mode
Remote
Location
United States
Posted
21 hours ago
SQLAWSETLAirflowGDPRHIPAAPythonRedshift

Job Description

Role - Data Engineer

Location - Remote

Contract - 6 Months CTH

  

 

Qualifications Required

Bachelor's degree in a computer-related field from an accredited college or university and five (5) or more years of experience in data engineering, building scalable and distributed ETL data pipelines in enterprise environments.

Experience building and operating scalable AWS-based data platforms and pipelines using services including Lambda, Glue, Athena, S3, Redshift, DMS, MWAA (Airflow), and Step Functions, supporting batch, CDC, and near real-time data processing.

Advanced proficiency in Python, SQL, and PySpark with hands-on experience developing reusable ETL/ELT frameworks, data warehouses, data marts, and integrations across databases, APIs, event streams, and analytics environments.

Experience implementing data quality, governance, and optimization best practices, including automated validation frameworks, Lake Formation and Glue Data Catalog, performance tuning, and cost optimization across AWS data services.

Strong communication skills with the ability to translate complex data concepts for business stakeholders;

Experience in healthcare, life sciences, and other highly regulated environments with HIPAA, GDPR, FDA, or similar compliance requirements preferred.

Experience with metadata management, data lineage, data observability, master data management, or enterprise data catalog solutions.

Knowledge with data modeling & analytical data model, schema design, schema evolution, and data structure optimized for reporting and analytics.

Knowledge of data lake and data warehouse architecture include data partitioning and columnar storage format such as Parquet.

Relevant AWS certification, such as AWS Certified Data Engineer – Associate, or an equivalent cloud or data engineering certification.

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