ADCI HYD

Fintech

DataEngineer

₹8–12L ~AI est. Hyderabad, Telangana, India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Data Engineer at ADCI HYD. Skills: Data engineering, AWS technologies, Data modeling, ETL. Design platform for secured access. Implement platform for secured access”

What You'll Achieve.

Deliver BI applications; Drive key business decisions

Industry & Context.

Fintech
Problems you'll solve

Analyze and solve problems at their root; Stepping back to understand broader context; Quantitative analysis; Business judgment

What They're Looking For.

Must Have

1+ years of data engineering experience, Experience with SQL, Experience with data modeling, Experience with warehousing, Experience building ETL pipelines, Experience with one or more query language, Experience with one or more scripting language

Nice to Have

Experience with big data technologies, Experience with any ETL tool

What You'll Do.

Design platform for secured access

Implement platform for secured access

Support platform for secured access

Interface with tax customers

Interface with finance customers

Interface with accounting customers

Collaborate with Finance Analysts

Recognize best practices in reporting

Help adopt best practices in reporting

Recognize best practices in analysis

Help adopt best practices in analysis

Support ad-hoc reporting

Support pre-built reporting

Own design of metrics

Own development of metrics

Own maintenance of metrics

Own design of reports

Own development of reports

Own maintenance of reports

Own design of analyses

Own development of analyses

Own maintenance of analyses

Own design of dashboards

Own development of dashboards

Own maintenance of dashboards

Tune application performance

Tune query performance

Understand data resources

Design data architecture

Scale data architecture

Improve reporting processes

Improve analysis processes

Automate support for datasets

Simplify support for datasets

Triage courses of action

Make use of quantitative analysis

Make use of business judgment

How You'll Work.

Team & Collaboration

Work with stakeholders; Work with Finance Analysts; Work with technical professionals

Full Job Description

External job description: Does the prospect of dealing with massive volumes of data excite you? Do you want to lead scalable data engineering solutions using AWS technologies? Do you want to create the next-generation tools for intuitive data access? Amazon's Finance Tech team needs a Data Engineer to shape the future of the Amazon finance data platform by working with stakeholders in North America, Asia and Europe. The team is committed to building the next generation big data platform that will be one of the world's largest finance data warehouses by volume to support Amazon's rapidly growing and dynamic businesses, and use it to deliver the BI applications which will have an immediate influence on day-to-day decision making. Members of the team will be challenged to innovate using the latest big data techniques. We are looking for a passionate data engineer to develop a robust, scalable data model and optimize the consumption of data sources required to ensure accurate and timely reporting for the Amazon businesses. You will share in the ownership of the technical vision and direction for advanced reporting and insight products. You will work with top-notch technical professionals developing complex systems at scale and with a focus on sustained operational excellence. We are looking for people who are motivated by thinking big, moving fast, and exploring business insights. If you love to implement solutions to hard problems while working hard, having fun, and making history, this may be the opportunity for you. Key job responsibilities Design, implement, and support a platform providing secured access to large datasets. Interface with tax, finance and accounting customers, gathering requirements and delivering complete BI solutions. Collaborate with Finance Analysts to recognize and help adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation. Model data and metadata to support ad-hoc and pre-built rep

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