Data Architect

Domain Architect Data Engineering

• Experience

  : Minimum of 13+ years of experience as a Data Architect in complex, large-scale data environments.

• SSIS, Databricks Expertise

  : Strong hands-on experience working with SSIS, Databricks, including using Apache Spark for data processing and optimization.

• ETL Tools

  : Proficient with various ETL tools and frameworks such as Informatica, Talend, or SSIS or DataBricks

• Big Data Technologies:

  In-depth knowledge of big data processing frameworks like Spark, Flink, Hadoop, Kafka, etc.

• NoSQL/MongoDB:

  Expertise in working with NoSQL databases, especially MongoDB, for large-scale data storage, retrieval, and optimization.

• Programming Skills:

  Proficient in SQL, Python or Java, Power shell for building data pipelines.

• SQL and NoSQL Proficiency:

  Strong knowledge of SQL and experience working with both relational databases and NoSQL databases like MongoDB.

• Data Modeling:

  Expertise in designing and implementing data models, including OLAP, OLTP, dimensional, and document-based models (NoSQL

• Data Reporting:

  Experience in integrating with Reporting platforms like Tableau, Qlik, etc

• Data warehousing:

  Data warehousing is a key part of ETL process, as it stores data from multiple sources in an organized manner and will be needed to build a repeatable ETL workflow to support many different data sources. Experience in building Datawarehouse,

  Datalakes in Snowflake.

• Redesign and refactor legacy custom ETL processes to reusable ETL workflows that can ingest diverse data sources to normalize data to standard JSON / XML output.

• Data Governance:

  Knowledge of data governance, security standards, and best practices for managing sensitive data.

• Version Control:

  Experience with Git or other version control systems for code management.

• Certification:

  Databricks certification, MongoDB certification, Snowflake SnowPro certification, or other relevant certifications in data engineering, cloud platforms (AWS, Azure or GCP or TKGI), or big data technologies.

• Soft Skills:

  Strong problem-solving skills, excellent communication, and the ability to work in a collaborative team environment.

• Analytical Mindset:

  Ability to translate business requirements into scalable, efficient, and reliable ETL solutions.
• Knowledge on AI/ML/GEN AI is desirable