Data Architect

Here is a refined Job Description (JD) for a Data Architect role with emphasis on AWS/GCP/Azure, Data Lakes, Warehouses, ETL, Streaming, Messaging Brokers, Data Modeling, System design and Code Reviews

Job Title: Data Architect
Location: Onsite Hyderabad Experience: 10+ Years Employment Type: Full-time Department: Data & Analytics

Position Overview
We are looking for a seasoned Data Architect to lead the design and implementation of scalable, high-performance data platforms across cloud ecosystems (AWS, GCP, or Azure). This role involves building cloud-native data lakes and warehouses, architecting robust ETL and streaming pipelines, and enforcing strong data modeling and engineering practices. You will be hands-on with coding, guide technical teams, and participate in code reviews to ensure delivery of enterprise-grade data solutions.

Key Responsibilities
Design and architect end-to-end data solutions using AWS, GCP, or Azure cloud services.

Build and manage large-scale Data Lakes and Data Warehouses (Redshift, BigQuery, Synapse, Snowflake).

Architect and optimize ETL/ELT pipelines for both batch and real-time data processing.

Integrate and manage messaging systems like Kafka, Pulsar, AWS Kinesis, or GCP Pub/Sub.

Define enterprise data models and ensure alignment with analytical and operational needs.

Write production-grade code and provide technical leadership through design and code reviews.

Collaborate with cross-functional teams to understand business needs and translate them into scalable data solutions.

Establish and promote data architecture best practices, standards, and documentation.

Support data governance, lineage, cataloging, and security practices.

Required Skills and Qualifications
10+ years of experience in data engineering and architecture roles.

Proven experience with cloud platforms: AWS (Glue, Redshift, S3), GCP (BigQuery, Dataflow, Cloud Storage), or Azure (ADF, Synapse, ADLS).

Strong expertise in building and managing data lakes, data warehouses, and streaming platforms.

Hands-on development in Python, SQL, Scala, or Java.

Proficient with streaming frameworks (Kafka, Pulsar, Flink, Spark Streaming).

Deep knowledge of data modeling techniques (normalized, dimensional, denormalized).

Experience with orchestration tools: Airflow, dbt, Dataform, or Dagster.

Excellent code review and mentoring skills.

Strong understanding of security, compliance, and data governance in cloud environments.

Preferred Qualifications
Experience migrating legacy data platforms to the cloud.

Familiarity with Lakehouse architectures (Delta Lake, Iceberg, Hudi).

Understanding of DataOps, CI/CD pipelines for data engineering.

Cloud certifications (AWS/GCP/Azure – Architect or Data Engineer track).