Data Architect

Role & responsibilities

Responsible for designing, developing ETL jobs, guides data engineers to implement data pipelines based on the architectural requirement, supports data test engineers in automating data validation jobs and configuring them as part of pipeline, evaluates tools, builds proof of concepts.

Role and Skills:

Must Have:-12+ years of overall experience with minimum 6 years solid experience in Data warehouse/Data Lake ETL/ELT jobs

-Experience designing ETL pipelines for complex Data Warehousing/ Data Lake projects

-Strong knowledge in SQL Server and Oracle Databases or any other equivalent RDBMS database

-Evaluate COTS/ Open-source product and recommend right fit solutions for given customer challenge

-Communicates technical architecture to other technical teams and leadership teams

-Work with Data Stewards & Business Analysts to understand and define data quality thresholds

-Good understanding about Data Quality, Data Modernization, and Data Governance -Understanding Meta data management, master data management and reference data management

-Experience in using Cloud data platforms such as Snowflake, Kafka, Databricks etc.

-Hands-on experience in big data analytics such as Hadoop, Apache Spark, Hive, Presto etc.-Understanding blob-based storage option in Cloud (AWS S3 or Azure Blob storage etc)

-Knowledge in Cloud based data services like RDS, Data Factory, AWS Glue etc.

-Exposure to Power.BI, Tableau, Qlix, Data.world-Experienced in automated data validation using RightData, DataGaps, ICEDQ or equivalent products

Preferred for NextGen:

-AI/ML Knowledge on building Intelligent data validations and eliminate data anomalies-Understanding in DataOps, Data Fabric and Data Mesh concepts

-Experience in any Data Orchestration tools such as Apache Airflow

-Certification in relevant area of expertise will be an added advantage

3 must haves

Data Engineering, DWH and Data Lake Design

Cloud Data Stack (Azure, AWS), MDM, Data Governance,

Good Communication