Senior Python Data Engineer

As a Senior Data Engineer within the Investment Group Technologies organization, you will lead the design, implementation, and successful delivery of large-scale, critical, and complex data architecture, storage, and pipelines that improve the lives of tens of millions of people every single day. You will design, implement, and automate data pipelines, sourcing data from many internal and external systems. You will build ETL processes to process large amounts of data in AWS, drive architectural plans, and implementation for future data storage, reporting, and analytic solutions. You will own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.

Responsibilities

You will design data models, and operate cloud-based data warehouses, and SQL/NoSQL/temporal database systems. you will be working closely with information security teams to adopt and implement security best practices for data pipelines and data servers. You will also provide insightful code reviews, receive code reviews constructively, and take ownership of outcomes ("you ship it, you own it"), working very efficiently and routinely with the team to deliver the right data for the UI through web services.

Skills

Must have

* BS in Computer Science or related field
* 7+ years of experience implementing big data processing pipelines (SQL / NoSQL) technology: Hadoop, Apache Spark, AWS Glue/Athena, Airflow, Serverless, etc.
* Coding proficiency in Python is essential.
* AWS knowledge and experience.
* Experience writing and optimizing advanced SQL queries in a business environment with large-scale, complex datasets.
* Experience in cloud-first design, preferably AWS (VPC, Serverless databases, and functions, dynamic autoscaling, container orchestration, etc.).
* Experience in data architecture, databases (e.g., MySQL, Oracle, PostgreSQL, DynamoDB, RDS Aurora), SQL and DDD/ER/ORM design.
* Interest and curiosity in emerging technologies on the web like GraphQL, web assembly, Lambda functions, MLaaS, etc.
* Knowledge of software engineering practices & best practices for the software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.