Note: The job is a remote job and is open to candidates in USA. RBA is a consulting partner that helps enterprise and mid-sized organizations transform their businesses through modern technology solutions. The Senior Data Engineer will architect and deliver modern data platforms supporting analytics, AI/ML, and business intelligence initiatives, while partnering with clients and engineering teams to develop scalable, secure, and high-performing data solutions.
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
- 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
- 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
Company Overview