Career

Responsibilities

Interface with internal business partners, program & product managers, understanding requirements and delivering vendor integrations.
Add and maintain vendor library integrations for our site properties.
Manage and maintain privacy components for our site properties.
Adopt and define the standards and best practices in vendor integration/tag management including data integrity, validation, reliability, and documentation.
Troubleshoot issues related to 3rd party vendor integrations.
Analyze and solve problems at their root, stepping back to understand the broader context.
Learn and understand GoDaddy’s revenue tracking platform and know when, how, and which to use and which not to use.
Keep up to date with advances in technologies and run pilots to design reviews.
Continually improve ongoing processes, automating or simplifying self-service support where possible.
Triage many possible courses of action in a high-ambiguity environment, making use of both quantitative analysis and business judgment.

Qualifications

Strong JavaScript experience required.
Good Node.JS experience required.
7+ years of front-end development experience with a focus on writing performant and optimized code required. Advance knowledge is preferred.
Google and Social Ad Platform experience preferred.
Experience working with browser inspector and performance tools is preferred.
Strong organizational and multitasking skills with ability to balance competing priorities.
Strong attention-to-detail and organizational skills.
Excellent communication (verbal and written) and interpersonal skills and an ability to effectively communicate with both business and technical teams.

Apply HERE

Responsibilities

Interface with our Business Analytics & data science teams, gathering requirements and delivering complete BI solutions.
Mentor junior engineers.
Model data and metadata to support discovery, ad-hoc and pre-built reporting.
Design and implement data pipelines using cloud/on-premise technologies
Own the design, development, and maintenance of datasets our BA teams will use to drive key business decisions.
Develop and promote best practices in data engineering, including scalability, reusability, maintainability, and usability.
Tune and ensure compute performance by optimizing queries, databases, files, tables, and processes.
Analyze and solve problems at their root, stepping back to understand the broader context.
Partner with a data platform team to establish SLAs and resolve any data/process issues.
Keep up to date with advances in big data technologies and run pilots to design the data architecture to scale with the increased data volume using AWS.
Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for datasets.
Triage many possible courses of action in a high-ambiguity environment, making use of both quantitative analysis and business judgment.

Qualifications

Bachelor’s degree in CS or related technical field.
10+ years of experience in data architecture and business intelligence
3 + years of experience in developing solutions in distributed technologies such as Hadoop, hive and spark
Experience in delivering end to end solutions using AWS services – S3, RDS, Kinesis, Glue, Redshift & EMR
Expert in data modeling, metadata management, and data quality.
SQL performance tuning.
Strong organizational and multitasking skills with ability to balance competing priorities.
Experience in programming using Python, Java or Scala
Excellent communication (verbal and written) and interpersonal skills and an ability to effectively communicate with both business and technical teams.
An ability to work in a fast-paced environment where continuous innovation is occurring and ambiguity is the norm.
Experience in SQL Server BI stack and with a BI reporting tool
Experience migrating from an on-prem to cloud data platform will be a plus

Apply HERE

Responsibilities:

Work with data and analytics experts to strive for greater functionality in our data systems and can install Airflow from scratch and configure and maintain administer it.
The engineer should be an independent guy and should keep up to date with the Airflow open-source community enhancements. He should work with other team members and communicate on planning to make sure nothing gets impacted because of the installation or configuration of Airflow
Create and maintain optimal data pipeline architecture,
Assemble large, complex data sets that meet functional / non-functional business requirements.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
Work with stakeholders including the Product, Data and Analytic teams to assist with data-related technical issues and support their data infrastructure needs.
Implement CI/CD pipelines

Requirements:

Experience with building data pipelines using EC2, EMR, RDS, Redshift, Spark, Python

Understands data and ability to discuss with analysts and translate to material that data engineers can easily understand
Understands and ability to develop data models for traditional relational and distributed technologies
Experience with SQL and AWS
Experience with engineering process (SDLC, data eng cycle, DataOps, DevOps)
Effective in driving meetings, discussions
Good project planning, execution skills

Apply HERE

Responsibilities:

Drive efficiency, effectiveness and results!!!
Create epics/stories/requirements so that the developers can act on; Maintain the backlog
Plan and execute large projects and fit it into incremental delivery model
Run scrum ceremonies (grooming, planning, standups and retros)
Run requirements, design and code reviews
Partner will analytics and other technology teams
Be responsible for deliverables
Contribute to prioritization, architectural decisions, approach selection and data modelling activities
Evangelize the data stack and solutions delivered across analytic partners
Manage relationships with stake holders, understand the requirements, prepare roadmap and set expectations
Provide operational metrics
Provide metrics on team performance (velocity etc.)

Requirements:

Experience with Data Solutions using Hive, Spark, S3, EMR, Airflow, Python
Understands data and ability to discuss with analysts and translate to material that data engineers can easily understand
Understands and ability to develop data models for traditional relational and distributed technologies
Experience with Rest APIs and strong SQL
Experience with engineering process (SDLC, data eng cycle, DataOps, DevOps)
Effective in driving meetings, discussions
Good project planning, execution skills

Apply HERE