Senior Engineer, Data Engineering

Full Time Job
Senior Engineer, Data Engineering

WWE has an Enterprise Data Warehouse and continues to focus on improving the data-driven decision-making and automation processes. This role will be reporting to the Vice President, Data Platform Engineering and supervise the team of ETL Developers, Data Engineers, QA, and Data analysts who build, enhance and optimize ETL (Extract, Transform, Load) jobs, implement data lake and warehouse solutions and manage their day-to-day tasks. The Senior Manager will be responsible for the continued success of the data warehouse release cycle process, prioritizing items for inclusion, and ensuring those tasks are completed per schedule. The candidate must have strong data lake, data warehouse, data pipeline design/development, data modeling, SQL, AWS Cloud, and Big Data Technologies experience.

You will have the opportunity to contribute to end-to-end platform design for our cloud architecture and work multi-functionally with operations, data science, and the business segments to build batch and real-time data solutions. The role will be part of the Data Platform Engineering team supporting WWE Corporate Marketing, Products, Content, and Consumer business units. This is also a hands-on position, requiring extensive experience developing and maintaining complex data warehouse and data transformation processes on AWS cloud as well as good decision making, leadership, time management, prioritization, and escalation skills are required to ensure all objectives are met

Key Responsibilities:

Oversee the on-going development of the enterprise data warehouse using inputs from the business end-user's perspective to produce timely and accurate information for management decision making and planning

Supervise the EDW/ETL team, including the design and development of the data warehouse

Evaluate EDW/ETL team members and provide input into the performance planning and evaluation process

Work with business stakeholders and data SMEs to clarify requirements and business rules

Responsible for the prompt, courteous, and efficient management of all support requests to the Data Warehouse team, including ad-hoc data analysis requests

Oversee efforts to design, develop, implement, and validate ETL/ELT processes

Architect analytical data layers (marts, aggregates, reporting, semantic layer) and define methods of building and consuming data (views, tables, extracts, caching) leveraging CI/CD approaches with tools such as Python and dbt.

Provide expertise and guidance in the creation and refinement of agile technical stories for data architecture and development

Work with Data Management to establish governance processes around meta-data to ensure an integrated definition of data for enterprise information, and to ensure the accuracy, validity, and reusability of metadata

Assist in developing long-term strategies and capacity planning for meeting future data warehouse and data automation needs

Experience in Delivering solutions using Agile methodologies and supporting tools like Jira

Experience in building CI/CD pipelines on AWS and Google Cloud

Conduct POC's for Data Integration tools, continuously assessing, automating, and evolving data Integration roadmap

Responsible for creating and maintaining inbound and outbound Data Delivery SLA's

Ability to implement PII data policies and principles to ensure data is secured, acceptable and accurate

Document and maintain all the processes and procedures pertaining to ETL and data warehouse usage/development of the organization, including a data dictionary

Education
& Technical Experience Requirements

Bachelor's in computer science, science, or similar technical degree

10+ years of hands-on experience in building data pipeline using traditional ETL tech stack and big data technologies

5+ years of experience with traditional ETL/ELT technologies such as Talend, Informatica, SSIS, MPP, and NoSQL Databases with the recent experience on AWS cloud technologies

3+ years of experience with AWS services including S3, Lambda, Redshift, EMR, and RDS databases such as MySQL

3+ years of Expertise in Snowflake data modeling, ELT using Snowflake SQL or Modern Data Replication tools (i.e., Fivetran), Snowflake Store Procedures / UDF / advanced SQL scripting, and standard Data Lake / Data Warehouse concepts.

3+ years of experience with Hadoop, Hive, PySpark, Airflow, and Streaming Technologies (Kinesis/Kafka)

3+ years of experience in programming languages such as Python, R, Java, C#

3+ years of team management experience

Experience designing, deploying and supporting production cloud services in AWS ecosystem including EC2, VPC, SQS, RDS, ELB, EBS, S3, KMS, Redshift

Experience in AWS MLOPS tools and understanding of the data science model development processes

Solid experience in data modeling, star/snowflake schemas design/development, and dimensional modeling

Proficient in Data warehousing theory, practice and combined with strong hands-on experience in data warehousing, frameworks development, and data architecture

Hands-on experience in managing and delivering high-performance ETL solutions

Must have experience in implementing the end to end data warehousing solution

Excellent communication and collaboration skills

Able to sell concepts and designs/benefits to multiple audiences

Able to work within a cross-functional team environment with people from multiple business units, vendors, countries, and cultures.

Experience in .Net, C#, Java, Web Development is a plus

Experience in Social Media Datasets such as Twitter, YouTube, Facebook, Instagram is a plus

Experience in Google Clickstream, DFP, or Adobe Analytics datasets is a plus

Experience in dealing with the Media content subscription-based datasets is a plus

AWS Cloud Certification is a plus

Experience in Media & Entertainment industry is a plus

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