Technical Account Manager

PAR Technology

1d•$90,000 - $110,000•Remote

About The Position

Bridg is seeking a Technical Account Manager/Partner (Data) Engineer for its Partner Engineering team. Reporting to the Director of Technical Operations and Delivery, this client-facing role serves as the primary technical liaison for strategic clients, owning their technical relationship from scoping and implementation through ongoing support. Partner Engineering works at the intersection of client success and technical execution to provide seamless data integrations, efficient onboarding, and long-term technical success. The role collaborates with Customer Success, Product, and Engineering to address complex data challenges and communicate clear, actionable guidance to clients. The position combines technical account management (70%) with data engineering (30%). Responsibilities include managing client relationships and expectations, explaining platform capabilities and integration practices, designing and optimizing data pipelines and ETL workflows, developing Python and SQL solutions, and troubleshooting issues across AWS services, pipelines, and codebases. The role also uses AI tools to support client-facing documentation, pipeline troubleshooting, and code review. The position is remote and available in New York, Texas, Philadelphia, Florida, North Carolina, Minnesota, Colorado, Georgia, and Illinois.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related technical field.
At least 3 years of experience in a technical role involving direct client interaction, such as Technical Consulting, Partner Engineering, or Solutions Engineering.
Exceptional communication skills and ability to explain complex topics to technical and non-technical audiences.
Strong SQL skills and experience with data platforms such as Snowflake, Redshift, and Athena.
Proficiency in Python and its data stack, including pandas, numpy, polars, pyspark, and boto3.
Deep experience with AWS cloud services, including core compute, storage, and analytics tools.
Demonstrated success working with large-scale datasets and data formats such as Parquet, ORC, and CSV.
Experience troubleshooting distributed systems and cloud services such as EMR, Lambda, S3, and Kubernetes.
Experience with Agile project management tools such as Jira and version control using Git/GitHub.
Client-focused mindset, strong problem-solving skills, and attention to detail.
Comfort leading technical discussions, debugging issues, and owning long-term client success.

Nice To Haves

Master's degree in Computer Science, Data Science, or equivalent experience.
At least 5 years of experience in a technical role involving direct client interaction, such as Technical Consulting, Partner Engineering, or Solutions Engineering.
Familiarity with alerting and monitoring tools such as Opsgenie and CloudWatch.
Familiarity with data orchestration tools such as Airflow.
Experience with Terraform, CloudFormation, or similar infrastructure-as-code tools.
Prior experience in a high-growth, client-centric startup or SaaS environment.
Hands-on experience with AI tools such as Claude or Snowflake Intelligence.

Responsibilities

Serve as the main technical liaison for clients and support their long-term success and satisfaction.
Translate complex technical concepts into clear, concise updates for non-technical audiences.
Work cross-functionally with internal teams to resolve technical issues and align on requirements.
Educate clients on platform capabilities, integration best practices, and data governance standards.
Proactively manage client communication, expectations, and roadmaps.
Document solutions and processes in Confluence or internal wikis.
Translate business requirements into technical solutions and communicate those solutions to clients.
Design, build, and optimize scalable data pipelines and ETL workflows.
Develop in Python using libraries such as pandas, numpy, polars, pyspark, and boto3.
Use AWS services including S3, EC2, Redshift, Athena, Glue, EMR, EventBridge, Batch, and CloudWatch.
Write efficient, production-grade SQL for data transformation and analysis.
Manage CI/CD pipelines using GitHub, Jenkins, and Docker.
Follow Agile practices using Jira and contribute to a DevOps culture.
Troubleshoot and resolve complex data issues across AWS services, data pipelines, and codebases.
Use AI tools such as Claude to accelerate client-facing technical documentation, automate data pipeline troubleshooting, and streamline SQL/Python code review.