Build a framework, no just pipelines, more of a liaison between data engineers and architect, build data
Pyspark, python (must be able to code, not just write scripts), at least 2 years with modern data: spark, snowflake (redshift or data lakes also works in lieu of snowflake), etc.
ETL/ ELT: dbt, airflow (Work flow mgmt.), quality great expectations
SQL knowledge to transfer to DB2: writing SQL and doing implementations for transformation logic
Documentation, doing the implementations, architects will socialize a solution with the data engineers, more of a work with data architect, present to socialize with the stakeholders
Database modeling experience
DevOps: Jekins, Gitlab required
Adobe Experience Platform: more of a ingestion into batch. Able to understand different patterns or ingestions: batch ingestion, micro batch ingestion, etc. Diff implementations with AEP integrations. In general, need to know how would it look on AWS for reference ingestions, etc.
Plus: informatica, snap logic, kafka, new database platforms such as Postgres
Team Size: <10 ppl in the architecture team, this resource will be working with 1-2 people in terms of data arch, diff implementations. Engineers: 8-9 will be using reference implementations
Tuesdays- Thursday: 2 days are onsite days, most of the team does 2 of these days
Some technical knowledge, good interpersonal skills, coding, etc.
Tech Data Architect specializing in Hands on data engineering work for our technology & business partners. You will be part of the Distribution & Marketing Solutions Architecture team and steer strategic technology direction, define target state architecture, roadmaps and help build reference implementations in partnership with our Platform Engineering teams.