This role is for one of the Weekday's clients
Min Experience: 7 years
Location: NOIDA, Gurugram, Delhi
JobType: full-time
We are seeking an experienced and highly skilled
Data Architect
to design, develop, and optimize scalable data architectures that support business analytics, data governance, and enterprise reporting. The ideal candidate will have strong hands-on technical expertise in Python and PySpark, deep understanding of modern data platforms, and proven experience building robust, secure, and high-performing data ecosystems. This role requires a strategic thinker who can translate complex business requirements into effective data models and scalable systems, while ensuring data quality, accessibility, and reliability across the organization.
Key Responsibilities
Lead the design and implementation of enterprise-level
data architecture
, including data pipelines, data models, and analytical frameworks.
Build and optimize
data ingestion, transformation, and processing pipelines
using PySpark, Spark SQL, and distributed computing technologies.
Architect and maintain
data lakes, data warehouses, and streaming-based data solutions
, ensuring efficiency, performance, and scalability.
Collaborate with cross-functional teams including data engineering, analytics, cloud infrastructure, and business stakeholders to define data roadmaps, standards, and governance practices.
Establish
data modeling standards
and best practices for structured, unstructured, and semi-structured data.
Drive
data quality, metadata management, and master data management
efforts to ensure data consistency and integrity.
Evaluate, recommend, and integrate new data management tools, platforms, and technologies aligned with industry best practices.
Ensure




security, compliance, and privacy
requirements are embedded into data solutions, supporting regulatory frameworks and audit processes.
Mentor and guide data engineers and analysts on architectural standards, performance tuning, and advanced data processing techniques.
Conduct performance tuning, optimization, and troubleshooting of large-scale distributed data systems and pipelines.
Required Skills & Experience
7–13 years of experience
in data architecture, data engineering, or related fields.
Robust programming skills in
Python
and expert-level proficiency in
PySpark / Apache Spark
.
Proven experience designing and implementing large-scale
data pipelines
and distributed data processing systems.
Hands-on experience with
big data ecosystems
(e.g., Hadoop, Spark, Hive, HDFS, Kafka).
Experience with
cloud data platforms
such as AWS, Azure, or GCP (e.g., Redshift, Snowflake, Databricks, BigQuery).
Strong understanding of
ETL/ELT frameworks
, workflow management tools, and orchestration systems (Airflow, DBT, etc.).
Deep knowledge of
data modeling techniques
including relational, dimensional, and NoSQL model designs.
Familiarity with
data governance
,
data quality frameworks
, and
metadata management
.
Excellent problem-solving, analytical thinking, and communication skills with the ability to simplify complex data challenges.
Ability to collaborate effectively with engineering, analytics, and business stakeholders.
Preferred Qualifications
Experience working in
product-led or high-growth technology environments
.
Knowledge of
machine learning data preparation
and real-time analytics.
Exposure to API-based data consumption and microservices architecture.

📌 Data Architect (Haryana)
🏢 Weekday AI
📍 Haryana