Create and manage the fundamental data infrastructure required for expanding and scalability of the acquisition marketing initiatives
Take ownership of a sizable amount of the marketing data from beginning to finish, including data intake, transformation, and visualization, as well as the design of the data architecture, to guarantee exceptional operational reliability and adaptability
Combine technical capabilities with business knowledge and communication abilities
Build a data architecture that meets business demands by collaborating with internal stakeholders to comprehend the business context.
To provide highly accurate and trustworthy business reporting, design, construct, and maintain crucial data pipelines and dashboards
Ensure SLAs are satisfied by supervising daily work execution and diagnosing/fixing problems with internal stakeholders
To guarantee that business requirements and ETL logic are compatible, identify data discrepancies, and maintain clear, up-to-date code
Own data import/export pipelines
Improve the data model and ETL code to increase pipeline effectiveness and data quality
Create and maintain new and existing Explores and Views to add to the Looker data models
Job Requirements:
Bachelor s/Master s degree in Engineering, Math, or Computer Science (or equivalent experience)
At least 3+ years of relevant experience as an analytics engineer
3+ years of experience in technical data analytics, business intelligence, or analytics engineering position
Extensive knowledge of SQL and ETL optimization methods, particularly in relation to cloud-based data warehouses like Redshift, Snowflake, and/or BigQuery
Knowledge of the command line and version control software (Git)
Knowledge of data pipeline management tools with dependency checking, like Airflow, as well as schema design and dimensional data modeling tools (dbt)
In-depth knowledge of data visualization tools, like Looker or Tableau
Extensive experience with LookML Development and AWS ecosystem, including Redshift
Demonstrable experience working with Python, the AWS ecosystem (Redshift, S3, Spectrum), and data ingestion technologies (Fivetran, Stitch, Alooma, or Matillion)
Ability to demonstrate tools, business intelligence, and attention to detail for data validation and QA
High level of motivation to be proactive and go above and beyond the task at hand
Experience working with digital and offline media data (such as Facebook, Google, programmatic, tv, and streaming audio)
Solid understanding of digital marketing measurement concepts (i.e. Multi-touch attribution)
Excellent communication skills, especially when explaining technical or sophisticated matters to less technical coworkers
Prior experience converting business needs into technical specifications to produce accurate, scalable, and performant data models
Fluent in spoken and written English communication skills