Senior Data Engineer

Paramount•Burbank, CA

22d•$115,920 - $173,880

About The Position

The Senior Data Engineer should possess a deep sense of curiosity and a passion for building data pipelines, data structures and data products and the ability to communicate data structures and tools throughout the Paramount Digital Media organization. The candidate for this role will use their skills in reverse engineering, analytics, and creative, experimental solutions to devise data and BI solutions. They will have experience supporting data pipeline development, which includes machine learning algorithms using disparate data sources. They will work closely with BI, Research, Engineering, Marketing, Finance, and Product teams to implement data-driven plans that drive the business. They will also be able to lead a project from inception to completion, as well as help mentor junior members of the team on standard processes and approaches around data.

Requirements

Bachelor's degree and 4+ years of experience in Data Engineering and Analytics fields or consulting roles with a focus on digital analytics implementations.
Experience with large scale data warehouse management systems such as BigQuery with advanced level understanding of warehouse cost management and query optimization
Proficient in Python.
Experience with Airflow or equivalent tools for orchestration of pipelines.
Experience with Data Modeling of performant table structures.
Able to write SQL to perform common types of analysis and transformations.
Strong problem-solving and creative-thinking skills.
Ability to design and implement technical solutions, maintain accurate documentation, and deliver training to impacted teams as needed.
Experience developing solutions to business requirements via hands-on discovery and exploration of data.
Excellent written and verbal communication skills, including the ability to communicate technical concepts to non-technical audiences, as well as translating business requirements into Data Solutions
Strong experience with ETL & ELT.
Experience building and deploying applications on GCP cloud platform.
Influences and applies data standards, policies, and procedures
Builds strong commitment within the team to support the appropriate team priorities
Knowledge of new and evolving technologies via formal training and self-directed education

Nice To Haves

Experience with BigQuery and other GCP technologies.
Experience with Docker and container deployment.
Experience with Marketing tools like Kochava, Braze, Branch, Salesforce Marketing Cloud is a plus.
Experience with exploratory data analysis using tools like iPython Notebook, Pandas & matplotlib, etc.
Familiarity in Hadoop pipelines using Spark, Kafka.
Familiar with GIT.
Familiar with Adobe Analytics (Omniture) or Google Analytics.
Digital marketing strategy including site, video, social media, SEM, SEO, and display advertising

Responsibilities

Works with large volumes of traffic data and user behaviors to build pipelines that enhance raw data.
Able to break down and communicate highly complex data problems into simple, feasible solutions.
Extract patterns from large datasets and transform data into an informational advantage.
Find answers to business questions via hands-on exploration of data sets via Jupyter, SQL, dashboards, statistical analysis, and data visualizations.
Partner with the internal product and business intelligence teams to determine the best approach around data ingestion, structure, and storage, and ensure successful implementation in partnership with the team.
Lead initiatives to improve data quality and effectiveness by contributing ideas and collaborating with engineering, BI teams, and business units to implement changes.
Ongoing development of technical solutions while developing and maintaining documentation, at times training impacted teams.
Early on collaboration with the team on internal initiatives to create strategies that improve company processes.
Look at ways of improving efficiency by staying current on the latest technology and trends and introducing team members to such.
Develop prototypes to proof out strategies for data pipelines and products.