Senior Data Engineer

🕒 September 26, 2025

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Rearc

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤖 Artificial Intelligence

Artificial Intelligence • Cloud

Rearc is a boutique, engineering-driven services firm specializing in cloud, data, and generative AI solutions. They are known for their innovation and engineering delivery excellence, empowering small teams to achieve significant results and foster creativity. Rearc offers services such as GenAI quickstart, secure data collaboration, data platform foundation, and cloud platform engineering. Their services are comprehensive and adaptable to meet the specific needs of their clients. Rearc has expertise in building foundational data platform capabilities, cloud governance, and the use of AWS products.

📋 Description

• Provide strategic vision and technical leadership in data engineering, guiding advanced data strategies • Design and architect complex data pipelines and scalable architectures using tools like Apache Kafka and Kubernetes • Optimize ETL processes, data modelling, and data warehousing for efficiency, scalability, and reliability • Collaborate closely with cross-functional teams and stakeholders to design and implement robust data solutions • Mentor and coach junior team members and foster growth in data engineering practices • Lead exploration and adoption of new technologies and methodologies to drive innovation and continuous improvement • Contribute to thought leadership through technical articles, conference presentations, and industry participation

🎯 Requirements

• 8+ years of experience in data engineering • Strong expertise in designing and implementing data warehouse and data lake architectures, particularly in AWS environments • Extensive experience with Python for data engineering tasks and familiarity with common libraries/frameworks • Proven experience with data pipeline orchestration using Airflow, Databricks, DBT or AWS Glue • Hands-on experience with data analysis tools and libraries such as PySpark, NumPy, Pandas, or Dask • Proficiency with Spark and Databricks (highly desirable) • Experience with SQL and NoSQL databases including PostgreSQL, Amazon Redshift, Delta Lake, Iceberg, and DynamoDB • Deep knowledge of data architecture principles and best practices in cloud environments • Proven experience with AWS services, AWS CLI, SDK, and IaC tools (Terraform, CloudFormation, or AWS CDK) • Deep expertise in ETL processes, data modelling, and data warehousing • Exceptional communication skills for technical and non-technical stakeholders • Demonstrated ability to quickly adapt to new tasks and roles in a dynamic environment

🏖️ Benefits

• Health Benefits • Generous time away • Maternity and Paternity leave • Educational resources and reimbursements • 401(k) plan with a company contribution