Senior Software Engineer, Measurement & Reporting

LG Ad Solutions•Denver, CO

4d•$135,000 - $220,000•Hybrid

About The Position

LG Ad Solutions is seeking a talented and motivated Senior Software Engineer I to join their Measurement and Reporting team. This role focuses on designing, building, and maintaining large-scale data platforms and pipelines that power reporting, analytics, and AI-driven solutions. The engineer will also contribute to the development of agentic AI applications for workflow automation and operational efficiency, with occasional work on frontend applications for end-to-end solutions. The ideal candidate is passionate about scalable data systems, AI technologies, and solving complex engineering challenges in the AdTech space.

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
5+ years of experience in data engineering, software engineering, or a related technical role.
Strong experience building and maintaining large-scale data pipelines and distributed data processing systems.
Proficiency in Python and SQL, with experience developing production-grade data solutions.
Experience with modern data platforms and technologies such as Databricks, Spark, Kafka, Airflow, Snowflake, BigQuery, Redshift, or similar technologies.
Strong understanding of data modeling, data warehousing, and data lake architectures.
Experience working with relational and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Redis).
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
Experience building APIs and backend services.
Familiarity with Generative AI technologies, AI agents, prompt engineering, retrieval-augmented generation (RAG), and agent orchestration frameworks.
Demonstrated ability to stay current with AI tools and emerging technologies, with a strong aptitude for rapidly learning and adopting new frameworks.
Proficiency in writing and maintaining unit tests, integration tests, and end-to-end tests.
Ability to coordinate and work with contractors/consultants while owning the quality and delivery of assigned projects.

Nice To Haves

Familiarity with AdTech.
Experience with Scala/PySpark and distributed data processing frameworks.
Experience with Databricks and Delta Lake.
Experience building production AI applications using frameworks such as LangGraph, LangChain, CrewAI, AutoGen, or similar technologies.
Familiarity with vector databases and semantic search technologies.
Experience with CI/CD pipelines and Infrastructure as Code
Familiarity with containerization (Docker) and orchestration platforms (Kubernetes).
Exposure to frontend technologies such as React, TypeScript, or modern JavaScript frameworks.
Experience with observability, monitoring, and data quality tools.

Responsibilities

Design, develop, deploy, and maintain scalable data pipelines, ETL/ELT workflows, and data processing systems supporting reporting, analytics, and machine learning applications.
Build and optimize batch and real-time data processing solutions using modern data engineering frameworks and cloud-native technologies.
Design and maintain data models, data warehouses, and data lakes to ensure high-quality, reliable, and accessible data.
Develop and maintain integrations between internal and external systems, ensuring efficient data movement and consistency across platforms.
Build and enhance agentic AI applications, leveraging LLMs, AI agents, orchestration frameworks, and automation workflows to solve business problems.
Collaborate with product, analytics, operations, and engineering teams to identify opportunities for AI-driven automation and intelligent decision-making.
Contribute to backend services and APIs that support data products, reporting applications, and AI-powered solutions.
Occasionally develop frontend features and dashboards to support internal and customer-facing applications.
Monitor, troubleshoot, and optimize data pipelines and AI systems for performance, reliability, scalability, and cost efficiency.
Implement data governance, quality checks, monitoring, and observability practices to ensure data integrity and operational excellence.
Conduct code reviews, provide constructive feedback, and promote engineering best practices across the team.
Mentor junior engineers and contribute to a culture of continuous learning, innovation, and technical excellence.