Role Overview:

As a Data Architect, you will be instrumental in shaping our enterprise data landscape, translating complex business needs into robust, scalable, and secure data solutions. You will lead the design, development, and governance of our data architecture, ensuring optimal performance, integrity, and accessibility of critical data assets.

This role involves close collaboration with data scientists, data engineers, product managers, and senior business stakeholders to define data strategies, implement cutting-edge data platforms, and drive data-driven innovation across the organization. Your contributions will directly impact our ability to derive actionable insights, enhance product offerings, and empower strategic decision-making, ultimately delivering significant value to our users and customers.

Key Responsibilities:

- Design and implement comprehensive enterprise data models, including conceptual, logical, and physical designs, to support diverse analytical and operational requirements, ensuring scalability and efficiency.

- Lead the architecture and optimization of complex Data Engineering pipelines and ETL/ELT processes, transforming raw data into high-quality, consumable datasets for various business intelligence and machine learning initiatives.

- Define and manage the overall Database Architecture strategy, including the selection, configuration, and performance tuning of relational, NoSQL, and data warehouse systems, ensuring data security and high availability.

- Establish and enforce data governance frameworks, standards, and best practices for data quality, metadata management, and data lifecycle, guiding engineering teams and fostering a culture of data excellence.

- Collaborate proactively with cross-functional teams and senior leadership to understand strategic objectives, translate them into technical data requirements, and deliver innovative solutions that drive measurable business outcomes.

Required Skillset:

- Demonstrated expertise in data architecture principles, advanced data modeling techniques (dimensional, relational, graph), and database design across various platforms (e.g., SQL, NoSQL, cloud data warehouses like Snowflake, Redshift, BigQuery).

- Proven ability to design, build, and optimize large-scale Data Engineering pipelines using modern ETL/ELT tools and frameworks (e.g., Apache Spark, Airflow, Kafka, cloud-native data services on AWS, Azure, or GCP).

- Strong understanding of data governance, data security best practices, data quality management, and compliance standards relevant to enterprise data environments.

- Exceptional analytical and problem-solving capabilities, with a track record of translating complex business challenges into effective, scalable data solutions.

- Excellent communication, presentation, and interpersonal skills, capable of articulating intricate technical concepts to both highly technical and non-technical audiences, fostering strong stakeholder relationships.

- Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related quantitative field.

- Ability to thrive in a dynamic, collaborative environment, working effectively with diverse teams from our Gurgaon/Gurugram office.