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Senior (12+ years), specialized data-platform role with remote posting reduces applicant density.
Core data engineering skills are transferable, though financial domain and enterprise reporting needs increase specificity.
Explicit 12+ years requirement plus mandatory data engineering, cloud, Python/Spark/SQL and platform experience.
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Lead design and implementation of scalable, modern data engineering solutions including data pipelines, models, and integrations supporting analytics and AI/ML use cases.
Define technical roadmap and lead modernization from legacy ETL/reporting platforms to cloud-native data architectures with focus on performance, reliability, and governance.
Provide technical leadership including code reviews, performance tuning, production support, and mentoring of data engineers across teams.
Bachelor’s degree in computer science, data engineering, analytics, or related field.
12+ years’ experience in software engineering, data engineering, or enterprise data platform development.
Strong proficiency with Python, SQL, distributed data processing, ETL/ELT development; experience with Spark preferred.
Experience with cloud-based data platforms, preferably AWS, and enterprise data warehouses/BI platforms such as Redshift, Snowflake, or SAP BusinessObjects.
Senior technical expert with track record designing and leading complex data solutions integrating multiple systems and business domains.
Experienced in cloud data platform modernization and advanced analytics enablement including data quality, governance, automation, and AI/ML readiness.
Demonstrates leadership through mentoring, stakeholder management, and driving adoption of engineering standards and best practices across distributed teams.