Lead Data Engineer - Solutioning

Advanced development skills in cross-platform coding languages such as SQL, Python, Java, and Scala.

SQL and scripting expertise for data extraction, transformation, and building performant datasets, with a focus on automation

Extensive experience with relational databases and NoSQL databases (e.g., Snowflake, Databricks, Oracle, MongoDB, DynamoDB, Redis)

Proficient in cloud technologies including AWS (e.g., Lambda, Kinesis, DMS, Managed Flink) and Google Cloud Platform (GCP) for data storage, processing, and analysis

Familiar with SQL, Python, cloud data platforms (AWS, Azure, or GCP), and modern data stack tools such as Snowflake, Databricks, Spark, Airflow, or dbt,

with a desire to further develop technical expertise in data engineering tools, methodologies, and emerging technologies

Serve as the primary technical counterpart to Product Managers, engaging early in the intake process to assess feasibility, clarify scope, and identify data dependencies

Translate business requirements and product requests into well-defined data solution briefs, including data sourcing strategy, transformation logic, and consumption patterns

Partner with Data Architects to translate solution requirements into architectural patterns and data model designs that align with enterprise standards

Engage in estimation and planning activities, providing sizing guidance and technical risk assessment for product intake requests

Lead the design, construction, and management of technology architecture, solutions, and software aimed at gathering, managing, and using both structured and unstructured data from various sources

Develop robust processes and structures to optimize data flow, routing, and storage, meticulously considering business and technical requirements, and deploying cloud and local storage solutions as necessary