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Bitrock is seeking a Data Engineer to evolve a fintech/wealth management data platform built on Redshift, Airflow, and dbt. You’ll balance fine-tuning existing components with modernizing legacy data pipelines, acting as a technical bridge between business requirements and scalable architecture.
You will design and maintain data infrastructure for ingestion and transformation, build analytical models, and support ML initiatives.
Bitrock is a high-end consulting and system integration company, strongly committed to offering cutting-edge and innovative solutions. Our tailored consulting services enable our clients to preserve the value of legacy investments while migrating to more efficient systems and infrastructure. We take a holistic approach to technology: we consider each system in its totality, as a set of interconnected elements that work together to meet business needs.
We thrive on overcoming challenges to help our clients reach their goals, by supporting them in the following areas: Data, AI & ML Engineering; Back-end Engineering, Platform Engineering, Front-end Engineering, Product Design & UX Engineering, Mobile App Development, Quality Assurance, FinOps, Governance. The effectiveness of our solutions also stems from partnerships with key technology vendors, like HashiCorp, Confluent, Lightbend, Databricks, and Meterian.
We are looking for a Data Engineer to join a high-impact project in the fintech/wealth management domain. In this role, you will contribute to the evolution of our client's data platform—built on Redshift, Airflow, and dbt—balancing fine-tuning of existing components with the modernization of legacy ones.
You are a technical problem-solver who can bridge the gap between business requirements and scalable data architecture while working seamlessly in an iterative environment.
As a Data Engineer, you will design, build, and maintain the data infrastructure responsible for ingestion, orchestration, and transformation. You will build analytical data models that guarantee high performance, scalability, and reliability, while reconciling large volumes of raw data from heterogeneous sources into coherent aggregates. Additionally, you will support machine learning and advanced analytics implementations, creating artifacts optimized for both human stakeholders and AI tools.
Our recruitment process has 3 stages: