Senior Data Engineer

RBA, Inc.; United States; On-site; USD 120,000 - 190,000; Full time

Job summary

RBA seeks a Senior Data Engineer to design and deliver scalable data platforms powering analytics, AI/ML, and BI initiatives. You will collaborate with client stakeholders, data scientists, and engineering teams to translate business needs into robust data solutions across cloud environments.

This client-facing role emphasizes architecture, ETL/ELT development, data quality and governance, and mentorship of junior engineers, with opportunities to influence strategy and contribute to practice

Qualifications

• 5+ years of experience in data engineering or modern data platform development.
• Strong experience designing and building scalable data solutions in a cloud environment.
• Expertise in SQL, data modeling, and modern data architecture patterns, medallion architecture
• Experience with at least one major cloud platform (Azure preferred; AWS or GCP acceptable)
• Hands-on experience with ETL/ELT frameworks and orchestration tools (Airflow, dbt, ADF, or similar)
• Familiarity with modern data platforms such as Databricks, Snowflake, Microsoft Fabric, or equivalent technologies
• Solid understanding of DevOps practices for data, including CI/CD and infrastructure-as-code
• Strong communication and interpersonal skills, with the ability to operate effectively in client-facing environments
• Ability to balance hands-on development with solution design and technical leadership

Responsibilities

• Design and build scalable, end-to-end data pipelines across structured, semi-structured, and unstructured data sources
• Support sales process for data-centric solutions
• Implement modern data architectures (e.g., lakehouse, data warehouse, data mesh) with strong data quality, governance, and security practices
• Develop and optimize ETL/ELT pipelines using modern data platforms (e.g., Databricks, Snowflake, Microsoft Fabric, or similar)
• Tune and optimize workloads for performance and cost efficiency across cloud-based data platform
• Implement real-time and streaming data solutions (Kafka, Kinesis, Event Hubs, or similar)
• Enable AI/ML use cases by building data pipelines for feature engineering and model integration
• Partner with client stakeholders to translate business needs into scalable technical solutions—and contribute to shaping solution strategy during engagements
• Contribute to DevOps best practices including CI/CD and infrastructure-as-code (e.g., Terraform)
• Mentor junior engineers and contribute to practice development and thought leadership

Skills

Data engineering

Cloud data architecture

Communication skills

Leadership

ETL/ELT development

Tools

Databricks

Snowflake

Airflow

dbt

Terraform

Microsoft Fabric

Power BI

Job description

RBA is a trusted consulting partner helping enterprise and mid-sized organizations transform their businesses through modern technology solutions. We blend strategic thinking with deep technical expertise to deliver scalable, high-impact outcomes aligned to our clients’ goals. Our team partners with some of the most recognized companies in our market, while fostering a culture that values collaboration, growth, and meaningful work.

We are seeking a Senior Data Engineer to join our growing Data & Analytics practice. This is a client-facing, consultative role for someone who combines strong technical expertise with the ability to build trust, influence decisions, and help shape winning solutions.

In this role, you will architect and deliver modern data platforms that power analytics, AI/ML, and business intelligence initiatives. You’ll work closely with client stakeholders, data scientists, and engineering teams to design scalable, secure, and high-performing data solutions across a variety of cloud and data technologies.

What You’ll D

• Design and build scalable, end-to-end data pipelines across structured, semi-structured, and unstructured data sources
• Support sales process for data-centric solutions
• Implement modern data architectures (e.g., lakehouse, data warehouse, data mesh) with strong data quality, governance, and security practices
• Develop and optimize ETL/ELT pipelines using modern data platforms (e.g., Databricks, Snowflake, Microsoft Fabric, or similar
• Tune and optimize workloads for performance and cost efficiency across cloud-based data platform
• Implement real-time and streaming data solutions (Kafka, Kinesis, Event Hubs, or similar
• Enable AI/ML use cases by building data pipelines for feature engineering and model integration
• Partner with client stakeholders to translate business needs into scalable technical solutions—and contribute to shaping solution strategy during engagements
• Contribute to DevOps best practices including CI/CD and infrastructure-as-code (e.g., Terraform)
• Mentor junior engineers and contribute to practice development and thought leadership

What You Bring

• 5+ years of experience in data engineering or modern data platform development
• Strong experience designing and building scalable data solutions in a cloud environment
• Expertise in SQL, data modeling, and modern data architecture patterns, medallion architecture
• Experience with at least one major cloud platform (Azure preferred; AWS or GCP acceptable)
• Hands-on experience with ETL/ELT frameworks and orchestration tools (Airflow, dbt, ADF, or similar
• Familiarity with modern data platforms such as Databricks, Snowflake, Microsoft Fabric, or equivalent technologies
• Solid understanding of DevOps practices for data, including CI/CD and infrastructure-as-code
• Strong communication and interpersonal skills, with the ability to operate effectively in client-facing environments
• Ability to balance hands-on development with solution design and technical leadership

Nice to Have

• Experience with Databricks and/or Spark-based data processing
• Databricks certification
• Experience with Snowflake
• Snowflake certifications
• Experience with Microsoft Fabric
• Microsoft certifications (e.g., Azure, Fabric-related certifications such as DP-600)
• Programming experience in Python or Scala
• Experience with enterprise data governance tools and frameworks
• Familiarity with vector databases and semantic search applications
• Experience supporting AI/ML workflows and cloud-based ML services
• Cloud certifications (Azure, AWS, or GPC)
• Experience with BI tools such as Power BI, Tableau, or Looker