Data Scientist - Senior

Role & responsibilities

Minimum 8+ years of hands-on experience in Data Engineering, Data Platform Engineering, Big Data, or related disciplines.

Minimum 3+ years of experience leading technical teams, projects, or major data engineering initiatives.

Proven experience building and supporting large-scale cloud-based data ingestion, transformation, and analytics platforms.

Experience developing end-to-end ETL/ELT solutions in Azure cloud environments.

Demonstrated success delivering high-performance and scalable distributed data processing solutions using Spark and Databricks.

Experience optimizing data pipelines, Spark workloads, and cloud infrastructure for performance, reliability, and cost efficiency.

Experience working with modern data lake, warehouse, and lakehouse architectures.

Experience implementing DevOps practices, CI/CD pipelines, and automated deployment processes.

Experience operating within Agile software development methodologies.

Experience partnering with data scientists, analysts, architects, and business stakeholders to deliver enterprise data solutions.

Nice to Have

Experience with Snowflake data platform and cloud-native data warehousing solutions.

Experience with Qlik Replicate or similar enterprise data replication technologies.

Experience supporting real-time analytics and streaming data architectures.

Experience implementing Infrastructure as Code (IaC) and platform automation frameworks.

Knowledge of data observability, lineage, and metadata management tools.

Azure Data Engineer Associate, Azure Solutions Architect, or similar cloud certifications.

Experience supporting AI, machine learning, and advanced analytics workloads on enterprise data platforms.

Exposure to multi-cloud data ecosystems and hybrid cloud architectures.