What are the responsibilities and job description for the Data Analytics Engineer at GFiber position at Sharvarok?
This role is Remote in US!!
This role is not eligible for immigration sponsorship or transfers.
Please email your resume to Svitlana at ssikora@google.com, ensuring you include where you discovered this job opportunity.
Role Description
As a Data Analytics Engineer for GFiber, you will be working with multiple stakeholders across the organization to provide quantitative support, define metric rules and logic, deliver useful tables and reports, model business scenarios, and solve a wide range of business problems. To do so, you will be expected to create new pipelines from scratch, merging broad financial and ERP data sets together into a cohesive technical infrastructure. You will be responsible for engineering foundational table resources using Google Cloud Platform (GCP): BigQuery, Dataform, LookML, Dataplex, etc. The pipelines, metrics, tools, and analyses you develop will be used by our leaders to make strategic decisions and serve as a key input in decision-making.
Responsibilities
Create foundational pipelines and data extractions with large data sets using SQL and other GCP technologies demonstrating comfort with software-engineering-level best practices and approaches to data pipelines and management.
Work with large, complex data sets to solve difficult analysis problems, assess the impact of initiatives, and create on-going tooling/resources to run the business.
Collaborate with cross-functional partners to understand business context for solutions, analysis, and tooling needed to become the single point of contact for all financial data engineering questions.
Undertake specific tasks, bugs, and maintenance work. Additionally, own complex projects, proving mastery through accuracy, timeliness, and volume of work, with minimal guidance.
Minimum Qualifications
Bachelor's degree or equivalent practical experience.
5 years of experience in analytics, data science, and/or computer science engineering.
5 Years of experience with using SQL, writing queries from scratch on a daily basis, data engineering, architecture, pipeline management, and Extract, Transform, Load (ETL).
Expertise using GCP tools.
Nice To Have
Experience in HTML, Python, or other coding languages.
Experience using data to identify opportunities for business improvement and defining/measuring the success of those initiatives.
Ability to use written and verbal communication to build relationships with cross-functional partners and conduct presentations for stakeholders, including executive leadership.
Ability to engage with PMO teams to prioritize, provide level of effort estimations, manage bug queues and bandwidth.
The US base salary range for this full-time position is between $105,600 - $154,900 bonus cash award benefits.
This role is not eligible for immigration sponsorship or transfers.
Please email your resume to Svitlana at ssikora@google.com, ensuring you include where you discovered this job opportunity.
Role Description
As a Data Analytics Engineer for GFiber, you will be working with multiple stakeholders across the organization to provide quantitative support, define metric rules and logic, deliver useful tables and reports, model business scenarios, and solve a wide range of business problems. To do so, you will be expected to create new pipelines from scratch, merging broad financial and ERP data sets together into a cohesive technical infrastructure. You will be responsible for engineering foundational table resources using Google Cloud Platform (GCP): BigQuery, Dataform, LookML, Dataplex, etc. The pipelines, metrics, tools, and analyses you develop will be used by our leaders to make strategic decisions and serve as a key input in decision-making.
Responsibilities
Create foundational pipelines and data extractions with large data sets using SQL and other GCP technologies demonstrating comfort with software-engineering-level best practices and approaches to data pipelines and management.
Work with large, complex data sets to solve difficult analysis problems, assess the impact of initiatives, and create on-going tooling/resources to run the business.
Collaborate with cross-functional partners to understand business context for solutions, analysis, and tooling needed to become the single point of contact for all financial data engineering questions.
Undertake specific tasks, bugs, and maintenance work. Additionally, own complex projects, proving mastery through accuracy, timeliness, and volume of work, with minimal guidance.
Minimum Qualifications
Bachelor's degree or equivalent practical experience.
5 years of experience in analytics, data science, and/or computer science engineering.
5 Years of experience with using SQL, writing queries from scratch on a daily basis, data engineering, architecture, pipeline management, and Extract, Transform, Load (ETL).
Expertise using GCP tools.
Nice To Have
Experience in HTML, Python, or other coding languages.
Experience using data to identify opportunities for business improvement and defining/measuring the success of those initiatives.
Ability to use written and verbal communication to build relationships with cross-functional partners and conduct presentations for stakeholders, including executive leadership.
Ability to engage with PMO teams to prioritize, provide level of effort estimations, manage bug queues and bandwidth.
The US base salary range for this full-time position is between $105,600 - $154,900 bonus cash award benefits.