Data Engineer

Robotics Technologies LLC; Dallas (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Robotics Technologies LLC in Dallas is seeking a Senior Data Engineer to build scalable data infrastructure across ingestion, processing, and delivery, closely collaborating with backend, BI, and ML teams.

You will own end-to-end data pipelines, leverage AI tooling, and ensure data quality, reliability, and timely delivery in a fast-moving environment.

Experience with Python, Spark, Airflow, and modern data architectures is required; familiarity with AI tools like Claude is a plus.

Qualifications

• Proficient in Python and SQL with experience in PySpark or Scala.
• Experience designing and maintaining ETL/ELT pipelines.
• Hands-on with data orchestration and event-driven architectures (Airflow, Kafka, AWS EventBridge).
• Familiarity with data lake/warehouse technologies like Snowflake, Redshift.

Responsibilities

• Design, build, and maintain scalable data pipelines across ingestion and processing.
• Optimize ETL/ELT workflows and resolve production bottlenecks.
• Collaborate with backend, BI, and ML teams for data integration.
• Implement CI/CD for data workflows and ensure end-to-end testing.
• Monitor health, reliability, and SLA adherence.

Skills

Python

SQL

PySpark

Scala

Unix scripting

Tools

Airflow

SnapLogic

DBT

Git

Jenkins

Docker

GitHub Actions

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

About the Role:

We're hiring an exceptional Senior Data Engineer with deep data engineering expertise and strong, hands-on AI skills. You'll build scalable data infrastructure across ingestion, transformation, orchestration, and delivery — collaborating with backend, BI, and ML teams — while actively using AI tooling (Claude, Cursor, and beyond) as a core part of how you engineer and ship. Strong ownership mindset, data quality focus, on-call reliability, and a genuine drive to adopt modern AI tooling are a must.

Responsibilities:

• Design, build, and maintain scalable data ingestion and processing pipelines using SQL , Spark, Hadoop, Airflow, SnapLogic, or similar tools
• Optimize existing ETL/ELT workflows and resolve bottlenecks in production jobs
• Integrate multiple structured and unstructured data sources from internal and external systems
• Design and implement event-driven data pipelines using event bus architectures (Kafka, AWS EventBridge, SNS/SQS, or similar)
• Build and maintain event producers, consumers, and stream processors for real-time and near-real-time data flows
• Manage event schema design, schema registry, and versioning to ensure backward compatibility across consumers
• Monitor event bus health, lag, throughput, and reliability; respond to failures before SLA breach
• Implement and manage CI/CD pipelines for data workflows using Git, Jenkins, or GitHub Actions
• Ensure robust job scheduling, monitoring, logging, and end-to-end testing of data pipelines
• Debug and resolve production issues before SLA breach; participate in on-call rotation
• Collaborate with backend and BI teams for API and data integration
• Design and develop schema definitions; support data warehouse/mart to integrate disparate data sources and make them available for analysis
• Support large data volumes and flexible provisioning of new data sources
• Contribute to data architecture design across the data landscape
• Write clean, reusable, well-tested Python and Shell code across the full software development lifecycle
• Gather functional requirements, develop technical specifications, and own project and test planning
• Work in Agile/Scrum environments; help align team priorities across the organization
• Leverage AI-assisted dev tools (Claude, Cursor .. etc) to accelerate delivery and code quality

Required Skills :

• Strong Python, Advanced SQL, PySpark or Scala, Unix scripting
• Data orchestration: Airflow, SnapLogic, DBT, or equivalent
• Event bus & streaming: Kafka, AWS EventBridge, SNS/SQS, Kinesis, or similar
• Data lake & warehouse: Snowflake, Delta Lake, Redshift, BigQuery
• CI/CD tooling: Git, Jenkins / GitHub Actions, Docker
• Experience with APIs for data exchange and integration
• Data quality mindset, ownership, and SLA awareness
• NoSQL, Neo4j, GraphQL is plus

Preferred / Nice to Have :

• Experience with AI/ML models and feature pipelines
• Exposure to BI platforms (Tableau, Power BI) or data serving for dashboards
• Spark Streaming or Flink for stateful stream processing

Skills :

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.