Data Engineer

About the role

As a Data Engineer at Rearc, you'll contribute to the technical excellence of our data engineering team. Your expertise in data architecture, ETL processes, and data modeling will help optimize data workflows for efficiency, scalability, and reliability. You'll work 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 technical teams and stakeholders will be essential as you support data-driven initiatives and contribute to their successful implementation.

What you'll do

• Collaborate with Colleagues: Work closely with colleagues to understand customers' data requirements and challenges, contributing to the development of robust data solutions tailored to client needs.

• Apply DataOps Principles: Embrace a DataOps mindset and utilize modern data engineering tools and frameworks like Apache Airflow, Apache Spark, or similar, to create scalable and efficient data pipelines and architectures.

• Support Data Engineering Projects: Assist in managing and executing data engineering projects, providing technical support and contributing to project success.

• Promote Knowledge Sharing: Contribute to our knowledge base through technical blogs and articles, advocating for best practices in data engineering, and fostering a culture of continuous learning and innovation.

We're looking for:

• 2+ years of experience in data engineering, data architecture, or related fields, bringing valuable expertise in managing and optimizing data pipelines and architectures.
• Solid track record of contributing to complex data engineering projects, including assisting in the design and implementation of scalable data solutions.
• Hands-on experience with ETL processes, data warehousing, and data modelling tools, enabling the support and delivery of efficient and robust data pipelines.
• Good understanding of data integration tools and best practices, facilitating seamless data flow across systems.
• Familiarity with cloud-based data services and technologies (e.g., AWS Redshift, Azure Synapse Analytics, Google BigQuery) ensuring effective utilization of cloud resources for data processing and analytics.
• Strong analytical skills to address data challenges and support data-driven decision-making.
• Proficiency in implementing and optimizing data pipelines using modern tools and frameworks.
• Strong communication and interpersonal skills enabling effective collaboration with cross-functional teams and stakeholder engagement.

Your first few weeks at Rearc will be spent in an immersive learning environment where our team will help you get up to speed. Within the first few months, you’ll have the opportunity to experiment with a lot of different tools as you find your place on the team.

Rearc is committed to a diverse and inclusive workplace. Rearc is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.