Requirements
The role requires strong data querying and processing skills using SQL, SAS, Oracle, Apache Spark or similar language. Proficiency in data visualization tools like Power BI, Business Objects, Crystal or similar is necessary. Experience with data warehousing and ETL concepts, cloud platforms (Azure, AWS), data modeling techniques, and knowledge of data governance, quality assurance, and compliance best practices are essential. Solid grasp of core computer science fundamentals relevant to performance-critical data engineering is also required.
Description
As a data analyst your main role is understanding business requirements and provide data mappingand analysis that forms the blueprint of data flow from raw source systems to a customized datamart, dashboards or any other API required for data consumption. You will play a crucial role in thedata management process, ensuring that data is collected, transformed, and made accessible foranalytical purposes. Your expertise in data technologies will enable the organization to makeinformed decisions and derive valuable insights from large datasets.Understanding the project requirements, by conducting Business Discovery Sessions Work with internal teams like system support teams, DBA and MIS teams to translate the existing requirements intothe desired mart and reports Prepare data mapping documents, needed for development of various layers of the data platform (raw – bronze,EDM – silver, project specific – gold) Support during various phases of the projects as needed by the data engineers, data modelers, QA testers and PowerBI developers Collaborating with other developers, data analysts, and stakeholders to ensure that the software meets the needs ofthe business or organization Technical SkillsStrong data querying and processing skills using SQL, SAS, Oracle, Apache Spark or similar languageData Visualization tools – Power BI, Business Objects, Crystal or similar toolData Warehousing and ETL concepts CompetenciesExpert-level proficiency in SQL, Python with SAS/R/Spark as plusDeep understanding of distributed data processing frameworks, particularly Apache Spark.Experience with cloud platforms (Azure, AWS) — including Object storage, compute, networking, and dataintegration services.Familiarity with data modeling techniques, including schema design, partitioning, and performance tuning.Experience working with structured and semi-structured data formats (e.g., JSON, Parquet, Avro, XML).Knowledge of data governance, quality assurance, and compliance best practices.Solid grasp of core computer science fundamentals (e.g., data structures, search algorithms, queues)relevant to performance-critical data engineering