Data Engineer – TM1/Planning Analytics
Company Name:-
ADCI – Karnataka
Job Location:-
Bengaluru, Karnataka
Job Summary:-
Experience with data modeling, data warehousing, and building ETL pipelines
Experience in writing and tuning SQL scripts
Experience with reporting tools like Tableau or other BI packages
Solid communication skills and team player
Demonstrated ability to manage and prioritize workload
Exhibiting knowledge of financial planning, budgeting and forecasting functions and related processes
Bachelors in Computer Science, Engineering, Statistics, Mathematics or related field
How often have you had an opportunity to be an early member of a team that is tasked with solving a huge customer need through disruptive and innovative technology?
The Team: WW Operations Finance is poised for a revolution.
Historically, automation and technical infusion has taken a back-seat to important financial functions such as controllership, financial oversight, risk mitigation, and strong investment analysis.
Finance is set to be the Chief Story Tellers, and along the way inject machine learning, BI, advanced analytics and technical tools built to suit finance and business needs.
The Financial Systems and Analytics Team (FSAT) is seeking a Data Engineer to help lead a flagship multi-year project to inject automated planning and reporting, predictive forecasting, and help shape an end UI, built on the AWS Data Lake.
We are the tech team that supports WW Amazon Operations one of the fastest growing, largest and most complex Supply Chains in the world.
This position requires a high level of technical expertise with data engineering concepts.
Responsibilities:Designing and implementing an analytical environment using third-party and in-house reporting tools, modeling metadata, building reports and dashboards.
Work with leading edge technologies like AWS resources including EC2, RDS, Redshift, Kinesis, EMR, Lambda etc.
You will be writing scalable queries and tuning performance on queries running over billion of rows of data.
Interface with other technology teams to extract, transform, and load data from a wide variety of data sources.
Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.
Dive deep to resolve problems at their root, looking for failure patterns and sugg
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