Data Engineer

Robotics Technologies

Dallas (TX)

On-site

USD 86,000 - 123,000

Full time

3 days ago

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Job summary

Robotics Technologies in Dallas, TX is seeking a Data Engineer to build trusted data pipelines and analytics environments that support program delivery and operational improvements.

You will create and maintain optimal data pipeline architecture, design cloud-based solutions with AWS tools, and orchestrate data workflows. The role interfaces with data scientists and policy analysts to enable reproducible research and robust modeling.

Qualifications

Self-directed approach and comfort supporting data needs across multiple teams, systems, and products.
Experience working with large, complex, and confidential datasets.
Understand policy-relevant research questions; evaluate data sources and develop analytics products that deliver actionable insights.
Ability to design and build data pipelines, integrate and transform data from multiple sources, identify and address data quality issues, and establish controls for responsible data use.

Responsibilities

Create and maintain optimal data pipeline architecture.
Design and implement cloud-based data solutions using AWS services including S3, Glue, Redshift, EMR, Athena, Kinesis and Lambda.
Build and maintain data orchestration workflows using Apache Airflow, AWS Step Functions, or similar services.
Assemble large, complex datasets aligned to functional and non-functional business requirements.
Engineer analytical data environments enabling advanced statistical analysis, predictive modeling, machine learning, and evidence-building activities.
Partner with data scientists, research analysts, and policy analysts to support reproducible research and statistical modeling through enterprise data assets.
Identify and implement internal process improvements, automate manual workflows, optimize data delivery, and redesign infrastructure for greater scalability.
Build ETL/ELT infrastructure to extract, transform, and load data from a wide variety of sources using SQL and big data technologies.

Skills

Data pipeline design

Cloud data solutions

Cross-team collaboration

Data quality management

Analytical thinking

Tools

AWS

Glue

Redshift

EMR

Athena

Kinesis

Lambda

Apache Airflow

AWS Step Functions

SQL

Big data technologies

Job description

Data Engineer role in Dallas, TX focused on building trusted data pipelines and analytics environments to support program delivery and operational improvements.

Responsibilities

Create and maintain optimal data pipeline architecture.
Design and implement cloud-based data solutions using AWS services including S3, Glue, Redshift, EMR, Athena, Kinesis, and Lambda.
Build and maintain data orchestration workflows using Apache Airflow, AWS Step Functions, or similar services.
Assemble large, complex datasets aligned to functional and non-functional business requirements.
Engineer analytical data environments that enable advanced statistical analysis, predictive modeling, machine learning, and evidence-building activities.
Partner with data scientists, research analysts, and policy analysts to support reproducible research and statistical modeling through enterprise data assets.
Identify and implement internal process improvements, including automating manual workflows, optimizing data delivery, and redesigning infrastructure for greater scalability.
Build ETL/ELT infrastructure to extract, transform, and load data from a wide variety of sources using SQL and big data technologies.

Requirements

Self-directed approach and comfort supporting data needs across multiple teams, systems, and products.
Comfort supporting data conversions tied to system modernization and/or replacement efforts.
Experience working with large, complex, and confidential datasets.
Understand policy-relevant research questions; evaluate data sources and develop analytics products that deliver actionable insights.
Ability to design and build data pipelines, integrate and transform data from multiple sources, identify and address data quality issues, and establish controls for responsible data use.
Ability to work with large, complex, and confidential datasets.

Technology & Tools