Staff Analytics Engineer - Data Analytics Team, Hyderabad

Global Sports Jobs Limited; Phoenix (AZ); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

A great place to work

Fast track growth opportunities

Job summary

Global Sports Jobs Limited seeks a Staff Analytics Engineer for the Commerce & Growth Analytics team at Warner Bros. Discovery.

You will design data models, partner with stakeholders to answer key business questions, and build scalable analytics solutions across pipelines, data tables, and visualizations. You will drive automation, contribute to data quality initiatives, and mentor junior engineers while working in a fast-paced, cross-functional environment with product, marketing, engineering,

Qualifications

• Bachelor's degree in a quantitative field (Computer/Data Science, Engineering, Mathematics, Statistics, etc.).
• 9+ years of relevant experience in BI/data engineering.
• SQL: clean, fast code; star schemas, SCDs, ELT/ETL.
• Transforming flawed data into trustworthy datasets; develop DAGs for batch processing millions of records.
• General-purpose programming (Python, Java, Go).
• Experience with Spark, Kafka, Hive.
• BI tools: Looker, Tableau.
• Git and CI/CD best practices.
• Experience with Agile workflows.
• Clear, concise documentation and strong communication.
• Ability to manage multiple projects with tight deadlines.

Responsibilities

• Design and implement data models to support flexible querying and visualization.
• Collaborate with Commerce and Growth stakeholders on business questions and analytics.
• Advance automation to reduce data manipulation and validation time.
• Build frameworks to multiply team productivity and enable other data teams.
• Create systematic solutions for data anomalies: alerting, root-cause analysis.
• Prepare data solutions for new product releases; troubleshoot data quality issues.
• Explore opportunities with innovative analytics methods.
• Develop and improve analytics development standards and best practices.
• Mentor junior data analytics engineers.

Skills

SQL

Python

Big Data

Data Visualization

Communication

Agile

DAGs

ETL/ELT

Looker

Tableau

Git

CI/CD

Cloud Platforms

Education

Bachelor's degree in quantitative field

MS or higher in quantitative field

Tools

Snowflake/Redshift

dbt

Spark

Kafka

Hive

Looker

Tableau

Databricks

Job description

About the Role

As a Staff Analytics Engineer, the role is responsible for data pipeline, data strategy, and data visualisation-related efforts for the Commerce & Growth Analytics team at WBD. The position involves managing projects from requirements gathering to planning to implementation of full-stack data solutions, from pipelines to data tables to visualisations. The role works closely with cross-functional partners to ensure that business logic is properly represented in the semantic layer and production environments. The team partners with Product, Marketing, Engineering, Finance, and other stakeholders to understand how customers discover, subscribe, activate, and retain streaming products.

Key Responsibilities

• Design and implement data models that support flexible querying and data visualization.
• Partner with Commerce and Growth stakeholders to understand business questions and build out advanced analytical solutions.
• Advance automation efforts that help the team spend less time manipulating and validating data and more time analysing.
• Build frameworks that multiply the productivity of the team and are intuitive for other data teams to leverage.
• Create systematic solutions for solving data anomalies: identifying, alerting, and root cause analysis.
• Work proactively with stakeholders to ready data solutions for new product and/or feature releases, with a keen eye for uncovering and troubleshooting any data quality issues or nuances.
• Identify and explore new opportunities through creative analytical and engineering methods.
• Create new or optimise existing analytics development standards and best practices.
• Mentor and provide guidance to junior data analytics engineers on the team.

Required Experience & Qualifications

• Bachelor's degree, MS, or greater in a quantitative field of study (Computer/Data Science, Engineering, Mathematics, Statistics, etc.).
• 9+ years of relevant experience in business intelligence / data engineering.
• Expertise in writing SQL (clean, fast code is a must) and in data-warehousing concepts such as star schemas, slowly changing dimensions, and ELT/ETL.
• Experience in transforming flawed/changing data into consistent, trustworthy datasets, and in developing DAGs to batch-process millions of records.
• Experience with general-purpose programming (e.g. Python, Java, Go), dealing with a variety of data structures, algorithms, and serialization formats.
• Experience with big-data technologies (e.g. Spark, Kafka, Hive).
• Advanced ability to build reports and dashboards with BI tools (such as Looker and Tableau).
• Proficiency with Git (or similar version control) and CI/CD best practices.
• Experience managing workflows using Agile practices.
• Expertise in writing clear, concise documentation and communicating with a high degree of precision.
• Ability to solve ambiguous problems independently and to manage multiple projects and time constraints simultaneously.
• Care for the quality of the input data and how the processed data is ultimately interpreted and used.
• Strong written and verbal communication skills, and strong organizational skills with the ability to act independently and responsibly.
• Self-starter, comfortable initiating projects from design to execution with minimal supervision, and able to balance multiple (and sometimes competing) priorities in a fast-paced, complex business environment while consistently meeting deadlines.
• Team player and relationship builder.

Preferred Skills

• Experience with OLAP databases such as Snowflake or Redshift.
• Experience with dbt or similar transformation and semantic-layer frameworks.
• Experience with digital products, streaming services, or subscription products.
• Experience with cloud data platforms such as Databricks.

Benefits & Perks

• A great place to work
• Fast track growth opportunities