Key Responsibilities - Work closely with product owners, analysts, software engineers and architects to understand the technical landscape and context of deliveries to refine complex functional and non-functional requirements and translate it into fit for purpose acceptance tests - Work on problems of diverse scope where analysis of data requires evaluation of identifiable factors and select methods to validate and automate the solution - Build test strategies and test plans validating the core business problem and translating them into tests around code functionality, data quality, performance, and security - Build and support generating or mocking of test data for exploratory analysis and running tests - Design and build automated tests / jobs of moderate to high scope and complexity across all stages of the data pipeline while demonstrating good coding & design practices and adhering to published coding standards and guidelines - Build and enhance data quality rules and platforms for observability across the data pipeline - Debug complex issues, resolve blockers and follow design documents with minimal or no supervision - Conduct data analysis activities such as source system analysis, data modelling, data dictionary collection, data profiling and source-to-target mapping ensuring delivery on business needs - Support in updating data inventories and registries as required to keep metadata and data lineage up-to-date, following agreed Data Governance standards, guidelines and principles Requirements / Qualifications - Degree in a relevant field such as Computer Science, Computational Mathematics, Computer Engineering or Software Engineering - Specialization or electives in a Data & Analytics field (e.g. Data Warehousing, Data Science, Business Intelligence) a nice-to-have - 2+ years Data Engineering experience with focus on quality & automation - Minimum 2+ years of testing, automation and support experience in analytics applications such as Data Lake and Data Warehouse (preferably using the Big Data stack and Microsoft Azure cloud infrastructure) - Seasoned in identifying quality issues across complex data pipelines running on big data technologies and defining rules for validating health of the data - Experienced in a wide variety of testing methods and tools covering functional, performance, security tests across individual jobs, pipelines and end to end across enterprise - Well versed in building automated checks running in a CI pipeline to validate the ETL / ELT jobs are performing as expected - Experience with batch and real-time data ingestion/integration tools and technologies handling massive quantities of data (structured and unstructured) - Exposed to data architecture concepts such as data modelling, Big Data storage, and dimensional modelling - Programming (Python or Scala) and SQL querying skills is required - Exposure to Spark & airline industry experience is nice-to-have - Technology Domain Key Technologies/Tools: Big Data & distributed processing (Spark, Hadoop/HDFS/Hive/H-Base/Oozie, Airflow, Apache Nifi, Azure ADLS/Databricks/Azure Data Factory, Elasticsearch, AVRO/PARQUET); Data Analysis/Modelling/Reporting (Snowflake, SQL, Data Vault 2.0, MicroStrategy, Power BI); Cloud (Microsoft Azure, Cloudera); Integration/Messaging (Spark Streaming, SnapLogic, TIBCO, Kafka); CI/CD (GIT, Bitbucket, Jenkins, Azure DevOps, Kubernetes, Docker, SonarQube, Gatling); Languages (Scala, Python) Preferred / Nice to have - Data & Analytics specialization/electives; Spark exposure; airline industry experience Selection process / Benefits (if stated) - Attractive tax-free salary and travel benefits exclusive to the industry, including discounts on flights and hotels stays around the world. ---