Data Engineer

Company Description

Forbes Advisor is a new initiative for consumers under the Forbes Marketplace umbrella that provides journalist- and expert-written insights, news and reviews on all things personal finance, health, business, and everyday life decisions. We do this by providing consumers with the knowledge and research they need to make informed decisions they can feel confident in, so they can get back to doing the things they care about most.

Forbes Advisor is looking to hire a Data Engineer to perform and Build core data products, Promote data-driven culture, Democratize insights through self-service, and Establish a single source of truth in business and customer metrics

If you're looking for challenges and opportunities similar to those of a startup, with the benefits of a seasoned and successful company, then read on:

Job Description

Responsibilities: 

• Assemble large, complex data that meet functional/non-functional business requirements.

• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing transformation for greater scalability, etc.

• Use the infrastructure/services required for optimal extraction, transformation, and loading of data from a wide variety of data sources using GCP and AWS services.

• Create data for analytics and CRM team members that assist them in building and optimizing our product.

• Work with stakeholders including the Product, Data and Design teams to assist with data-related technical issues and support their data requirement needs.

Requirements: 

• Bachelor’s degree with Minimum 5+ years of experience working in globally distributed teams successfully

• Must have experience working on Spark, Kafka, and Python

• Apply experience with cloud storage and computing for data pipelines in GCP (GCS, BQ, composer, etc)

• Write pipelines in Airflow to orchestrate data pipelines

• Experience handling data from 3rd party providers: Google Analytics, Google Ads etc.

• Strong analytic skills related to working with unstructured datasets.

• Experience in manipulating, processing and extracting value from large disconnected datasets.

• Experience with software engineering practices in data engineering, e.g. release management, testing, etc and corresponding tooling (dbt, great expectations, …)

• Basic knowledge on dbt

• Experience with data governance, privacy and security

• Basic ML exposure & know-how

• supporting teams as they migrate through guidelines, support and adherence to good practices.

• Dynamically adapt to fluid situations to deliver the intended results

• Strong interpersonal and conflict resolution skills

• Ability to form productive relationships quickly and create the spheres of influence required for transformational changes

• Excellent verbal and written communication skills

Perks:

• Day off on the 3rd Friday of every month (one long weekend each month)

• Monthly Wellness Reimbursement Program to promote health well-being

• Paid paternity and maternity leaves

Responsibilities: 

• Assemble large, complex data that meet functional/non-functional business requirements.

• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing transformation for greater scalability, etc.

• Use the infrastructure/services required for optimal extraction, transformation, and loading of data from a wide variety of data sources using GCP and AWS services.

• Create data for analytics and CRM team members that assist them in building and optimizing our product.

• Work with stakeholders including the Product, Data and Design teams to assist with data-related technical issues and support their data requirement needs.

Requirements: 

• Bachelor’s degree with Minimum 5+ years of experience working in globally distributed teams successfully

• Must have experience working on Spark, Kafka, and Python

• Apply experience with cloud storage and computing for data pipelines in GCP (GCS, BQ, composer, etc)

• Write pipelines in Airflow to orchestrate data pipelines

• Experience handling data from 3rd party providers: Google Analytics, Google Ads etc.

• Strong analytic skills related to working with unstructured datasets.

• Experience in manipulating, processing and extracting value from large disconnected datasets.

• Experience with software engineering practices in data engineering, e.g. release management, testing, etc and corresponding tooling (dbt, great expectations, …)

• Basic knowledge on dbt

• Experience with data governance, privacy and security

• Basic ML exposure & know-how

• supporting teams as they migrate through guidelines, support and adherence to good practices.

• Dynamically adapt to fluid situations to deliver the intended results

• Strong interpersonal and conflict resolution skills

• Ability to form productive relationships quickly and create the spheres of influence required for transformational changes

• Excellent verbal and written communication skills

Perks:

• Day off on the 3rd Friday of every month (one long weekend each month)

• Monthly Wellness Reimbursement Program to promote health well-being

• Paid paternity and maternity leaves

Additional Information

All your information will be kept confidential according to EEO guidelines.