Job Description

External Description: Working Model : Temporary full time for 1 year Report to : Senior Data Engineer We Are EA Electronic Arts is a global leader in digital interactive entertainment. Our game franchises are offered as both packaged goods products and online services delivered through Internet-connected consoles, personal computers, mobile phones, and tablets. EA has more than 275 million registered players and operates in 75 countries. Opportunity Ahead Player Insight Network (PIN) is the central telemetry solution that helps EA to make great games across all platforms and titles. We, Player Insight Network Quality Verification Team, are looking for a data engineer responsible for Extract Transform Load (ETL) logic validation through the use of test automation and database testing. You will work with our partners to ensure quality data in player engagement and gameplay telemetry from source to dashboard reporting. Besides applying best software engineering practice in data engineering space, SQL and scripting language, you will work with an amazing team of data craft practitioners in continuously driving high quality in our data product portfolios. EA Hyderabad is looking for a Data Engineer with a love for data. You will be responsible for planning, building and deploying data quality solutions for EA. The Data Engineer will be a subject matter expert in building data quality solutions using modern ETL technologies. You will leverage modern tools and technologies to store, analyse petabytes of data and solve complex business problems. You will collaborate with product, business and engineering teams to build & deliver the most optimal solution. Main Responsibilities Creation of test plans by reviewing data pipeline feature design spec Create test cases using DBT to validate ELT pipelines quality Create test cases using SQL & python in internal test case automation framework to ensure data quality Work with data analytics solution team to understand data requirements, Entity Relationship Diagram (ERD) and implementation of ETL logic Design effective test strategy to validate end-to-end data quality based on data requirements and needs Perform root cause analysis on failed test cases and communicate those to stakeholders Understand the design and architecture of data pipelines and come up with test solutions Identify and communicate test coverage gaps on raw data to the stakeholders Define data quality KPIs & metrics to provide executive summary Participate in scrum ceremonies (Sprint planning, daily stand up, review, retrospective) Analyze and improve test coverage based on feedback provided by downstream stakeholders Identify new, creative methods to increase data pipelines testing efficiency Enhance existing data pipelines quality processes Work with the product, business and engineering teams to Identify new opportunities for data acquisition Build analytical tools and programs to empower the business teams make decisions based on data Must Have Skills Excellent command over querying and analysing data using various query languages native to the storage system (e.g., SQL CQL, MQL, Hive, etc.) Good understanding of SQL and NoSQL database concepts & applications, data modelling techniques (3NF, Dimensional) Proven experience in tuning databases and queries for optimal performance Experience in programming languages used in data systems - Python or R or Java Experience in ingesting data from various sources in formats such as JSON, XML, CSV. Experience in data visualisation tools such as Tableau, Power BI, etc. Experience in working using agile methodologies. Prior experience in using tools such as Gitlab, JIRA, Confluence, etc. Ability to debug and test complex data pipelines Experience with identifying data quality rules and applying data validation techniques Good understanding of data lifecycle & quality applications Good understanding of software quality assurance concepts, debugging processes and practices3+ years relevant industry experience in data engineering role who has Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field Desirable Skills Building Statistical models and Machine Learning Algorithms Real-time data acquisition & processing frameworks (e.g., Apache Storm, Apache NiFi, Apache Spark)

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