Financial Analyst FP&A

Symbiotic Services

8d•Hybrid

About The Position

Symbiotic Services is seeking a Senior Data Engineer on behalf of a confidential client based in Plano, Texas. This role will help design and support a modern cloud-based data platform that enables scalable analytics, reliable data pipelines, and improved business insights across the organization. The ideal candidate has strong experience building data pipelines, working with cloud platforms, and collaborating with cross-functional teams to deliver high-quality data solutions.

Requirements

7+ years of professional software development or data engineering experience
5+ years of SQL experience, including dimensional data modeling and schema design in relational data warehouses
5+ years of ETL/ELT pipeline development and maintenance using relational databases
Experience with ETL tools such as dbt and Airflow
Strong proficiency in Python for data manipulation and scripting
Experience designing and optimizing large-scale data pipelines and architectures
Experience deploying production systems in cloud environments (AWS or Azure)
Strong communication skills and ability to collaborate across technical and business teams

Nice To Haves

Experience with Snowflake and AWS storage services (S3, RDS, Glacier)
Familiarity with BI and analytics tools such as Tableau, Power BI, Domo, or Astronomer
Experience with metadata management, dependency management, and workload orchestration
Knowledge of data security practices including encryption at rest
Experience supporting retail or multi-location operational environments
Bachelor’s degree in Mathematics, Economics, Engineering, Computer Science, or another technical field (advanced degree a plus)

Responsibilities

Design, build, and maintain scalable data pipelines using tools such as dbt and Airflow to support reliable data ingestion, transformation, and delivery
Architect and optimize batch and streaming data workflows in cloud environments using services such as AWS, Snowflake, S3, and RDS
Manage large and complex datasets to support a wide range of analytics and operational use cases
Implement monitoring, logging, and alerting for data workflows to ensure reliability and minimize downtime
Partner with stakeholders across departments including Operations, Finance, Supply Chain, and leadership teams to understand data needs and support analytics initiatives
Translate business requirements into scalable technical solutions
Collaborate with data analysts, data scientists, and BI developers to deliver meaningful insights
Support initiatives to improve data accessibility, standardization, and quality
Develop and maintain data validation frameworks and quality checks to ensure accuracy and reliability
Implement data security best practices, including encryption and secure data transmission
Maintain metadata management and data lineage tracking to support transparency and governance
Identify opportunities to improve data pipeline efficiency, infrastructure automation, and delivery processes
Support the evolution of the organization’s data architecture to meet new business and product needs
Troubleshoot issues related to data integration, storage, and performance