Data Engineer (Analytics) at Meta
New York, New York, USA -
Full Time


Start Date

Immediate

Expiry Date

12 Oct, 25

Salary

279400.0

Posted On

13 Jul, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Data Modeling, Maintenance, Python, Data Analytics, Mathematics, Programming Languages, Statistics, Computer Science, Deliverables, Applied Sciences, Data Warehouse, Information Systems, Mapreduce

Industry

Information Technology/IT

Description

MINIMUM QUALIFICATIONS

  • Requires a Bachelor’s degree(or foreign degree equivalent) in Computer Science, Engineering, Information Systems, Mathematics, Statistics, Data Analytics, Applied Sciences, or a related field and 60 months of experience in the job offered or in a related occupation.
  • Requires 60 months of experience involving each of the following:

    1. Features, design, and use-case scenarios across a big data ecosystem


      1. Custom ETL design, implementation, and maintenance


        1. Object-oriented programming languages


          1. Schema design and dimensional data modeling


            1. Writing SQL statements


              1. Analyzing data to identify deliverables, gaps, and inconsistencies


                1. Managing and communicating data warehouse plans to internal clients


                  1. MapReduce or MPP system


                    1. Python

                      For those who live in or expect to work from California if hired for this position.

                    Responsibilities
                    • Design, model, and implement data warehousing activities to deliver the data foundation that drives impact through informed decision making.
                    • Design, build and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains.
                    • Collaborate with engineers, product managers and data scientists to understand data needs, representing key data insights visually in a meaningful way.
                    • Define and manage SLA for all data sets in allocated areas of ownership.
                    • Create and contribute to frameworks that improve the efficacy of logging data, while working with data infrastructure to triage issues and resolve.
                    • Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data quality issues, and evolve governance processes within allocated areas of ownership.
                    • Solve challenging data integration problems utilizing optimal ETL patterns, frameworks, query techniques, and sourcing from structured and unstructured data sources.
                    • Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts.
                    • Influence product and cross-functional teams to identify data opportunities to drive impact.
                    • Work on problems of diverse scope where analysis of data requires evaluation of identifiable factors.
                    • Demonstrate good judgment in selecting methods and techniques for obtaining solutions.
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