Data Architect - Data Engineering 4D

Overview

Senior Principal Consultant - Data Architect in Data Engineering. Design and implement cloud data modernization solutions, translating business requirements into scalable, secure, high-performing data architectures.

What you'll do

• Collaborate with stakeholders to understand business requirements and translate them into data architecture strategies and solutions.
• Design and develop scalable, secure, and high-performing data architectures in the cloud, leveraging cloud technologies and services.
• Modernize legacy data systems and migrate them to cloud-based architectures, ensuring smooth transition and minimal disruption.
• Collaborate with data engineers, data scientists, and other IT professionals to design and implement data pipelines, data transformation processes, and data integration solutions.
• Ensure data governance principles and best practices are implemented, including data quality controls, data privacy, and compliance.
• Optimize data platforms for performance, scalability, and cost efficiency, monitoring and troubleshooting any issues that may arise.
• Stay updated with the latest trends and advancements in cloud technologies and data architecture, continuously enhancing knowledge and skills.
• Provide guidance and mentorship to junior team members, fostering a culture of learning and growth.
• Act as a subject matter expert in data architecture and cloud technologies, providing recommendations and insights to stakeholders and senior management.
• Lead RFP responses by working with the Sales, Vertical and competency teams.
• Groom the team members in the pre-sales area.

What you'll need

• In-depth knowledge and experience in designing and implementing scalable, secure, and high-performing data Lakehouse architectures in the cloud using Databricks.
• Proficiency in cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP), including their data services like AWS Glue, Azure Data Factory, or Google BigQuery.
• Expertise in modernizing legacy data systems and transitioning them to cloud-based architectures using industry best practices.
• Strong understanding of data integration techniques, including ETL (Extract, Transform, Load) processes, data pipelines, and data streaming using Python, Kafka for streams, PySpark, DBT, and ETL services provided by cloud providers and SQL/PLSQL.
• Familiarity with various database technologies, both relational and non-relational, such as SQL databases, NoSQL databases, data lakes, and data warehouses.
• Strong hands-on knowledge in Data Modelling techniques using ERWIN.
• Knowledge of data governance principles and practices, including data quality, data lineage, data privacy, and compliance.
• Understanding of data security principles, including encryption, access controls, and data masking techniques.
• Proficiency in programming languages such as Python, Java, or Scala, and experience with scripting languages like SQL or Shell scripting.
• Excellent communication and collaboration skills to effectively work with stakeholders, business users, and technical teams.
• Ability to lead/coordinate medium to large scale RFPs and construct end-to-end big-data, analytics technical solutions and articulate them using PowerPoint or Word documents.
• Participate in client presentations and present the solutions prepared.
• At least one Databricks certification (Associate or Professional) is mandatory for this role.

Nice to have

• Hybrid cloud domain exposure including end-to-end data architecture experience.

Details

• Location: Gurugram, India.
• Work mode: Hybrid.
• Work shift: Flex Time (India).
• Job type: Regular.
• Language: English (Required), Proficient - C2.