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Strong employer brand and metro locations, but senior specialized role reduces applicant density.
Core data engineering skills are transferable, though financial product context increases domain preference.
Senior Principal title plus mandatory hands-on cloud, SQL, data modeling and governance implies strict screening.
Translate business product requirements into technically actionable and build-ready data engineering user stories with clear acceptance criteria.
Collaborate closely with product owners, data engineers, solution architects, and platform teams to ensure technical feasibility and alignment of cloud data, analytics, and automation initiatives.
Contribute hands-on to data analysis, SQL querying, schema design, pipeline validation, data quality checks, and delivery process improvements to drive reliable and scalable data solutions.
Strong hands-on experience with SQL and data analysis on large datasets.
Solid understanding of cloud data platforms such as AWS, Azure, or GCP.
Familiarity with data lakes/lakehouses, ELT/ETL pipelines, streaming or batch data processing, and data modeling techniques.
Work Experience Required: Not explicitly mentioned in the JD.
Experience working in data engineering, analytics engineering, or platform engineering teams within Agile/DevOps environments.
Capable of bridging the gap between product and engineering teams with a strong technical understanding and clear communication skills.
Comfortable working in a hybrid in-office/remote model and able to engage in in-person collaboration at least three days per week.