Location
Los Angeles, CA | United States
Job description
Data Engineer VIAJP00000864
A leading digital streaming network is seeking a Data Engineer. The successful candidate will work closely with BI, Research, Engineering, Marketing, Finance, and Product teams to implement data-driven plans that drive the business. The ideal candidate has good communication skills and possesses the ability to convey knowledge of data structures and tools . The company offers a great work environment!
Data Engineer Pay and Benefits:
- Hourly pay: $65-$75/hr (Pay varies based on candidate's location and experience)
- Worksite: Leading digital streaming network. ( Remote, Candidates must be located in the United States)
- W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program
- 40 hours/week, 12 Month Assignment
Data Engineer 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. Then, work with the team to ensure these are implemented correctly.
- Contribute ideas on how to make our data more effective and work with other members of the 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 collaborate 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.
- Mentor members of the team and department on best practices and approaches.
- Lead initiatives in ways to improve the quality of our data as well as make the data more effective, with other members of engineering, BI teams, and business units to implement changes.
- Able to break down and communicate highly complex data problems into simple, feasible solutions.
- Influence and apply data standards, policies, and procedures.
Data Engineer Qualifications:
- Bachelor's degree and 3+ years of work 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 for 1+ years with an advanced level understanding of warehouse cost management and query optimization
- Proficient in Python.
- Experience developing solutions to business requirements via hands-on discovery and exploration of data.
- Experience with Apache Airflow or equivalent tools for orchestration of pipelines.
- Experience with ETL & ELT.
- Experience building and deploying applications on the GCP cloud platform.
- Experience with Snowflake, Redshift and other AWS technologies preferred.
- Experience with Docker and container deployment preferred.
- Experience with Data Modeling of performant table structures preferred.
- Experience with Marketing tools like Kochava, Braze, Branch, and Salesforce Marketing Cloud is a plus preferred.
- Experience with exploratory data analysis using tools like iPython Notebook, Pandas & Matplotlib, etc. preferred.
- Able to write SQL to perform common types of analysis and transformations.
- Strong problem-solving and creative-thinking skills.
- Demonstrated development of ongoing technical solutions while developing and maintaining documentation, at times training impacted teams.
- Exceptional 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
- Builds strong commitment within the team to support the appropriate team priorities
- Stays current with new and evolving technologies via formal training and self-directed education
- Familiarity in Hadoop pipelines using Spark, Kafka preferred.
- Familiar with GIT preferred.
- Familiar with Adobe Analytics (Omniture) or Google Analytics preferred.
- Digital marketing strategy including site, video, social media, SEM, SEO, and display advertising preferred.
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