Data Architect

Grid Dynamics; Chennai District, Bengaluru, Hyderabad; On-site; INR 1,700,000 - 2,500,000; Full time

Job summary

Grid Dynamics in Chennai is seeking a Data Engineer with 12-16 years of experience, including 4+ years as a Data/Big Data Architect. The role includes designing data architectures, enhancing data quality, and leading presales activities to assess client requirements and define solutions.

Candidates should have strong expertise in AWS and SQL, alongside hands-on experience in Python and big data frameworks like Spark and Kafka. This role offers opportunities for mentoring and establishing best practices.

Qualifications

• 12-16 years of overall experience in data engineering/analytics, with 4+ years as a Data/Big Data Architect.
• Proven presales exposure: client workshops, solution design, RFP/RFI responses.
• Practical experience on at least one major cloud platform (AWS, Azure, or GCP).

Responsibilities

• Design and own end-to-end data architectures including data lakes and streaming pipelines.
• Lead presales activities: assess client requirements and contribute to proposals.
• Collaborate with data engineers and application architects for implementation.

Skills

Experience with AWS (S3, EMR, running Spark jobs on K8s or EKS, Glue, Athena)

Extensive experience with Apache Spark

Hands-on experience in Python

Experience with Apache Airflow

Experience with Apache Iceberg

Hands-on experience with Hadoop stack (YARN, HDFS, Hive)

Strong expertise in SQL (analytical queries, performance tuning)

Strong understanding of data modeling (OLTP, OLAP, dimensional modeling)

Ability to communicate complex data solutions clearly

Tools

Apache Kafka

Hadoop ecosystem

ETL/ELT pipelines

Job description

Total Experience - 11years-15years

Location- Bangalore/Chennai/Hyderabad

Requirements for the candidate

Desired data engineering skills

• Experience with AWS (S3, EMR, running Spark jobs on K8s or EKS, Glue, Athena)
• Extensive experience with Apache Spark
• Hands-on experience in Python
• Experience with Apache Airflow
• Experience with Apache Iceberg
• Hands-on experience with Hadoop stack (YARN, HDFS, Hive) will be a plus.

Essential functions

Key Responsibilities

• Design and own endtoend data architectures including data lakes, data warehouses, and streaming pipelines using big data technologies (e.g., Spark, Kafka, Hive) on public cloud platforms.
• Define canonical data models, integration patterns, and governance standards to ensure data quality, security, and compliance across the organization.
• Lead presales activities: assess client requirements, run discovery workshops, define solution blueprints, size and estimate effort, and contribute to RFP/RFI responses and proposals.
• Build and review PoCs/accelerators using SQL and Python (e.g., PySpark, notebooks) to demonstrate feasibility, performance, and business value to customers.
• Collaborate with data engineers, BI/ML teams, and application architects to ensure the designed architecture is implemented as intended and is cost‑efficient, scalable, and reliable.
• Establish best practices for data security, access control, and lifecycle management in alignment with regulatory and enterprise policies.
• Monitor and continuously optimize data platforms for performance, reliability, and cost, leveraging cloudnative services and observability tools.
• Provide architectural guidance and mentoring to engineering teams; review designs and code for critical data components.

Required Skills Experience

• 12-16 years of overall experience in data engineering/analytics, with 4+ years as a Data/Big Data Architect.
• Strong expertise in SQL (analytical queries, performance tuning) and Python for data processing and automation.
• Hands-on experience with big data frameworks and tools such as Spark, Kafka, Hadoop ecosystem, distributed file systems, and modern ETL/ELT pipelines.
• Practical experience on at least one major cloud platform (AWS, Azure, or GCP) with services such as data lakes, warehouse services (Redshift/Snowflake/BigQuery/Synapse), and orchestration tools.
• Proven presales exposure: client workshops, solution design, RFP/RFI responses, effort estimation, and building PoCs or demos.
• Strong understanding of data modeling (OLTP, OLAP, dimensional modeling), data governance, security, and compliance.
• Ability to communicate complex data solutions clearly to both technical and business stakeholders.