Talend Architect

LocationMumbai, Maharashtra, India
SeniorityLead
DepartmentJonali
Company size1,001–5,000 people
PostedMay 6, 2026 · 5mo ago
Verified live1d ago
At a glanceSummarised by Seekless from the posting.
Strong experience in Talend Data Integration / Talend Cloud (Qlik)
Expertise in ETL/ELT, data modeling, and data warehousing concepts
Hands-on experience with SQL and databases (Oracle, SQL Server, etc.)
Experience with cloud platforms (AWS / Azure / GCP)
Experience in data quality, governance, and metadata management
Good understanding of APIs and integration patterns
Knowledge of Big Data tools (Spark, Hadoop) is a plus
Experience with Snowflake / Databricks
Exposure to CI/CD, Git, DevOps practices
Knowledge of real-time/streaming data (Kafka, etc.)
Skills
Talend
Qlik
ETL
ELT
SQL
Oracle
SQL Server
AWS
Azure
GCP
Spark
Hadoop
Snowflake
Databricks
CI/CD
Git
DevOps
Kafka
About the role
We are looking for a skilled Talend Architect to design and implement scalable data integration solutions using Talend (Qlik). The candidate will be responsible for building robust data pipelines, ensuring data quality, and defining enterprise data architecture.
Responsibilities
🔷 Key Responsibilities
•
Design and implement end-to-end ETL/ELT pipelines using Talend
•
Define data architecture for data warehouse, data lake, and integrations
•
Ensure data quality, governance, and data lineage
•
Lead and mentor Talend developers and data engineers
•
Optimize performance of data jobs and pipelines
•
Collaborate with business and technical teams for data requirements
•
Work on cloud-based data platforms (AWS/Azure/GCP)
•
Establish best practices, standards, and reusable frameworks
Requirements
🔷 Required Skills
•
Strong experience in Talend Data Integration / Talend Cloud (Qlik)
•
Expertise in ETL/ELT, data modeling, and data warehousing concepts
•
Hands-on experience with SQL and databases (Oracle, SQL Server, etc.)
•
Experience with cloud platforms (AWS / Azure / GCP)
•
Knowledge of Big Data tools (Spark, Hadoop) is a plus
•
Experience in data quality, governance, and metadata management
•
Good understanding of APIs and integration patterns
Nice to have
🔷 Good to Have
•
Experience with Snowflake / Databricks
•
Exposure to CI/CD, Git, DevOps practices
•
Knowledge of real-time/streaming data (Kafka, etc.)