Senior Data Engineer, Architect

This is a fully remote position, open to applicants in Texas.

📋 Description

• Design, construct, and sustain scalable data pipelines and workflows across contemporary cloud data platforms such as Snowflake, Databricks, Microsoft Fabric, or similar alternatives.

• Execute ELT/ETL processes with an emphasis on data quality, performance, reliability, and maintainability.

• Assemble and transform large, intricate datasets to fulfill both functional and non-functional business requirements.

• Develop and enhance data models to support analytics, reporting, and AI/ML applications.

• Operate across cloud environments (AWS, Azure, GCP) and their associated data services.

• Participate in solution design discussions with architects; provide an engineering perspective on feasibility, complexity, and implementation trade-offs.

• Assist in defining data pipeline patterns, platform configurations, and engineering standards within the project.

• Identify areas for enhancing data infrastructure: automate manual tasks, improve data delivery, and redesign for increased scalability and performance.

• Create analytics tools and data products that reveal actionable insights for clients across critical business metrics.

• Facilitate integration with BI and visualization tools such as Power BI, Tableau, Looker, Qlik, or similar platforms.

• Ensure data products are thoroughly documented, governed, and prepared for downstream utilization.

• Engage in client discovery and requirements-gathering sessions; offer an engineering perspective on feasibility, complexity, and implementation strategies.

• Assist in pre-sales and scoping activities alongside Architects and Pre-Sales teams to validate that proposed solutions are technically feasible prior to any commitments.

• Collaborate directly with client technical teams throughout the project lifecycle; establish credibility through engineering excellence and clear communication.

• Effectively manage multiple client engagements at various stages of the implementation lifecycle.

• Work alongside architects, solution owners, and client technical teams to achieve agreed-upon outcomes.

• Mentor junior data engineers; share insights and elevate the engineering standards of the teams you collaborate with.

• Clearly communicate technical progress, obstacles, and decisions to both technical and non-technical stakeholders.

⛳️ Requirements

• Bachelor's Degree or equivalent experience and/or military background.

• 5+ years of experience in data engineering or roles focused on cloud data platform development.

• 6+ years of advanced SQL expertise across various database environments and data modeling methodologies.

• Practical experience in developing on modern cloud data platforms such as Snowflake, Databricks, or similar; must have production-grade implementation experience, not just familiarity.

• Proficient with cloud data stacks on AWS, Azure, and/or GCP (e.g., EMR, Redshift, Glue, Kinesis/Kafka, Azure Data Factory, Synapse, BigQuery, Dataproc).

• Strong background in building data pipelines using Spark; skilled in Python and/or Scala.

• Experience with data pipeline orchestration tools (Airflow, dbt, or similar).

• Knowledge of lakehouse architectures, data mesh/fabric patterns, and contemporary data modeling techniques.

• Familiarity with AI-ready data engineering—designing pipelines and data foundations that cater to GenAI, Agentic AI, and ML workloads.

• Excellent communication abilities; capable of collaborating with both technical teams and business stakeholders across client projects.

🏝️ Benefits

• Health insurance

• 401k matching

• Paid time off

• Flexible working hours

• Professional development opportunities