Staff Analytics Engineer - Data Analytics Team, Hyderabad

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.

• 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.

• 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.

• 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.

• A great place to work
• Fast track growth opportunities