At Rearc, we're committed to empowering engineers to build awesome products and experiences. Success as a business hinges on our people's ability to think freely, challenge the status quo, and speak up about alternative problem-solving approaches. If you're an engineer driven by the desire to solve problems and make a difference, you're in the right place!

Our approach is simple — empower engineers with the best tools possible to make

an impact within their industry.

We're on the lookout for engineers who thrive on ownership and freedom, possessing not just technical prowess, but also exceptional leadership skills. Our ideal candidates are hands-on-keyboard leaders who don't just talk the talk but also walk the walk, designing and building solutions that push the boundaries of cloud computing.

As a Senior Data Engineer at Rearc, you'll play a pivotal role in establishing and maintaining technical excellence within our data engineering team. Your deep expertise in data architecture, ETL processes, and data modelling will be instrumental in optimizing data workflows for efficiency, scalability, and reliability. You'll collaborate closely with cross-functional teams to design and implement robust data solutions that meet business objectives and adhere to best practices in data management. Building strong partnerships with both technical teams and stakeholders will be essential as you drive data-driven initiatives and ensure their successful implementation. 

What You Bring

• 8+ years in data engineering, with proven experience across various architectures, technology stacks, and use cases.

• Expertise in designing and implementing data warehouse and lake architectures.

• Extensive experience in writing and testing Python and or Java. Familiarity with libraries such as Requests, Selenium, and Luigi is a plus.

• Proven experience with data pipeline orchestration platforms such as Airflow, Prefect, or AWS Glue.

• Hands-on experience with data analysis tools like NumPy, Pandas, Dask etc. 

• Proficiency with Spark, Databricks, or EMR is a major plus.

• Experience with SQL and NoSQL databases and data warehouses, including Postgres, RedShift, Delta Lake, and DynamoDB.

• In-depth knowledge of data architecture principles and best practices.

• Proven experience with cloud services on AWS, GCP, or Azure. Proficient in using CLI, SDK, and Infrastructure as Code (IaC) tools.

• Experience with IaC tools such as Terraform, CloudFormation, or AWS CDK.

• Exceptional communication skills, with the ability to articulate complex technical concepts to both technical and non-technical stakeholders.

• Demonstrated ability to quickly adapt to new tasks and roles in a dynamic environment.

What You'll Do

• Strategic Data Engineering Leadership: Provide strategic vision and technical leadership in data engineering, guiding the development and execution of advanced data strategies that align with business objectives.

• Architect Data Solutions: Design and architect complex data pipelines and scalable architectures, leveraging advanced tools and frameworks (e.g., Apache Kafka, Kubernetes) to ensure optimal performance and reliability.

• Drive Innovation: Lead the exploration and adoption of new technologies and methodologies in data engineering, driving innovation and continuous improvement across data processes.

• Technical Expertise: Apply deep expertise in ETL processes, data modeling, and data warehousing to optimize data workflows and ensure data integrity and quality.

• Collaboration and Mentorship: Collaborate closely with cross-functional teams to understand requirements and deliver impactful data solutions. Mentor and coach junior team members, fostering their growth and development in data engineering practices.

• Thought Leadership: Contribute to thought leadership in the data engineering domain through technical articles, conference presentations, and participation in industry forums.