Data Engineer Job

About the role

Armstrong is seeking a Data Engineer to design, build, and maintain scalable data pipelines and infrastructure that enable advanced analytics, AI, and data-driven decision-making across the organization. The ideal candidate has strong technical skills, experience working with modern data platforms, and a passion for solving complex data challenges.

What You'll Do

• Design and Develop Data Pipelines: Build and optimize data pipelines for batch and real-time data ingestion, transformation, and delivery. Use LLMs to automate routine tasks such as generating boilerplate code, writing documentation, and creating ETL workflows from natural language descriptions.
• Data Modeling and Data Lakehouse Development: Design and implement efficient, scalable data models to support analytics, reporting, and machine learning initiatives.
• Data Architecture and Harmonization: Design and build scalable data architecture - bringing in and marrying data from disparate systems including structured, semi-structured, and unstructured data ensuring quality data. Use the semantic understanding of LLMs to identify and correct errors in unstructured data.
• ETL/ELT Development: Develop robust ETL/ELT workflows using modern tools (e.g., dbt, Airflow, Databricks, Glue).
• Data Integration: Ingest and integrate data from multiple internal and external sources (APIs, databases, cloud services).
• Cloud Data Infrastructure: Manage and optimize data environments on platforms such as AWS, Azure, or GCP (e.g., Databricks, Snowflake, etc).
• Data Quality & Governance: Implement data validation, quality standards, governance frameworks, lineage, and monitoring processes to ensure accuracy and reliability. Apply LLMs to analyze log files and data patterns to identify potential issues, detect anomalies, and perform root cause analysis.
• Collaboration: Partner with data scientists, analysts, and business stakeholders to deliver reliable, well-structured datasets.
• Automation & Optimization: Continuously improve data workflows for scalability, cost efficiency, and performance.

What Will Make You Successful

Technical Skills:

• Proficiency in SQL and at least one programming language (Python, Scala, or Java).
• Experience with data lakehouse technologies (Databricks, Snowflake).
• Familiarity with data pipeline/orchestration tools.
• Knowledge of cloud services (AWS, Azure, GCP).
• Experience with CI/CD, version control (Git), and infrastructure-as-code is a plus.
• Experience with SAP BW, Datasphere, Business Data Cloud.
• Experience supporting machine learning or advanced analytics pipelines.
• Experience with LLMs and Prompt Engineering.

Soft Skills:

• Strong problem-solving and analytical skills.
• Excellent communication and collaboration abilities.
• Ability to work in a fast-paced, agile environment.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (Master's preferred).
• 5+ years of experience as a Data Engineer or similar role.

Pay

The estimated base salary range for this role is $125,000 to $145,000 per year. Individual pay is based upon location, skills and expertise, experience and other relevant factors.

Benefits

• Medical, dental, prescription drug, and life insurance
• 401k match
• Long-term disability coverage
• Vacation and sick time
• Product discount programs
• Personal development to grow your career based on your strengths and interests
• Casual work environment with recognition program and service awards
• Fitness center and lunchtime cafe
• Working culture that balances individual achievement with teamwork and collaboration

Schedule

Full-Time