ETL Developer

Rightdirectiontech; Baltimore (MD); On-site; USD 110,000 - 170,000; Full time

Job summary

Rightdirectiontech is seeking a data engineer to design, build, and maintain robust data pipelines and infrastructure in the AWS ecosystem. The role focuses on data modeling, ETL, and scalable architectures to support analytics and reporting across business units.

You will work with UI/APIs teams, business analysts and stakeholders to ensure timely, accurate data delivery and compliance with regulatory requirements.

Qualifications

• Design, develop and maintain data pipelines for structured and unstructured data.
• Build robust data architectures including data lakehouses, data lakes, warehouses and marts.
• Develop data reliability, quality checks and ETL efficiency measures.
• Prepare data for modeling and analytics.

Responsibilities

• Design and implement scalable data models to support applications, analytics and BI.
• Optimize data warehousing solutions and manage data migrations in AWS.
• Develop and maintain ETL pipelines using AWS Glue and related services.
• Ensure data integrity and timeliness across pipelines and systems.
• Integrate data from multiple sources and coordinate with stakeholders to meet requirements.
• Monitor performance, reliability and scalability of data architectures.
• Document data processes, controls and architectures.

Skills

ETL pipelines

Data modeling

AWS

Data warehousing

Stakeholder collaboration

Tools

AWS Glue

Amazon Redshift

RDS

DocumentDB

Job description

Description

Position Description: Responsible for designing, building, and maintaining data pipelines and infrastructure to support data-driven decisions and analytics. The individual is responsible for the following tasks:

A. Design, develop and maintain data pipelines, and extract, transform, load (ETL) processes to collect, process and store structured and unstructured data

B. Build data architecture and storage solutions, including data lakehouses, data lakes, data warehouse, and data marts to support analytics and reporting

C. Develop data reliability, efficiency, and qualify checks and processes

D. Prepare data for data modeling

E. Monitor and optimize data architecture and data processing systems

F. Collaboration with multiple teams to understand requirements and objectives

G. Administer testing and troubleshooting related to performance, reliability, and scalability

H. Create and update documentation

Role and Responsibilities: Design and implement robust, scalable data models to support the application, analytics and business intelligence initiatives.

Optimize data warehousing solutions and manage data migrations in the AWS ecosystem, utilizing Amazon Redshift, RDS, and DocumentDB services.

Develop and maintain scalable ETL pipelines using AWS Glue and other AWS services to enhance data collection, integration, and aggregation.

Ensure data integrity and timeliness in the data pipeline, troubleshooting any issues that arise during data processing.

Integrate data from various sources using AWS technologies, ensuring seamless data flow across systems.

Collaborate with stakeholders to define data ingestion requirements and implement solutions to meet business needs.

Monitor, tune, and manage database performance to ensure efficient data loads and queries.

Implement best practices for data management within AWS to optimize storage and computing costs.

Ensure all data practices comply with regulatory requirements and department policies.

Implement and maintain security measures to protect data within AWS services.

Lead and mentor junior data engineers and team members on AWS best practices and technical challenges.

Collaborate with UI/APIs team, business analysts, and other stakeholders to support data-driven decision-making.