Analytics Engineer

Job Description

About Us Started in 2019, STAGE is an entertainment platform for regional cultures known for producing premium quality content in Indian languages to reinforce, protect and validate people?s sense of identity for their culture and heritage. We currently focus on Haryanvi, Rajasthani and Bhojpuri languages. Our mobile apps have 15 Mn+ downloads and 4 Mn+ paying customers globally. That makes STAGE the biggest media platform in these regions. In 2023, STAGE was also featured on Shark Tank India S2. Watch our story here . Overview As a Analytics Engineer, you will lead data pipeline, data strategy, and data visualization-related efforts for the Data & Analytics organization at STAGE. You?re an engineer who not only understands how to use big data in answering complex business questions but also how to design semantic layers to best support self-service vehicles. You will manage projects from requirements gathering to planning to implementation of full-stack data solutions (pipelines to data tables to visualisations). You will work closely with cross-functional partners to ensure that business logic is properly represented in the semantic layer and production environments, where it can be used by the wider Product Analytics team to drive business insights and strategy. Responsibilities Design and implement data models that support flexible querying and data visualisation. Partner with Product stakeholders to understand business questions and build out advanced analytical solutions. Advance automation efforts that help the team spend less time manipulating & validating data and more time analysing. Build frameworks that multiply the productivity of the team and are intuitive for other data teams to leverage. Participate in the creation and support of analytics development standards and best practices. 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. Requirements Bachelor's degree in Engineering 4-8 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, ELT/ETL, and MPP databases Experience in using dbt to build transformations. 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 serialisation formats Advanced ability to build reports and dashboards with BI tools (such as Looker and Tableau) Experience with analytics tools such as Athena, Redshift/BigQuery, Splunk, etc. Proficiency with Git (or similar version control) and CI/CD best practices Experience in managing workflows using Agile practices Ability to write clear, concise documentation and to communicate generally with a high degree of precision Ability to solve ambiguous problems independently Ability 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 Experience with digital products, streaming services, or subscription products is preferred Strong written and verbal communication skills Must Have dbt, Snowflake Good To Have Airflow, Dimension Modelling, Star Schema, Kimball Warehouse, Facts and Dimensions, Data-bricks, Reverse ETL, Looker