Cloud Engineer

InfoVision Inc

5 - 7 years

18 - 20 Lacs

Pune

Posted:5 hours ago| Platform:

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Skills Required

snow flake schema schema snowflake oracle microsoft azure data warehousing etl informatica cloud platforms data architecture data pipeline data engineering sql server sql star schema cloud technical design postgresql gcp aws etl informatica etl development architecture

Work Mode

Work from Office

Job Type

Full Time

Job Description

Critical Skills to Possess:

5+ years of experience
in data engineering or ETL development.
5+ years of hands-on experience with Informatica.
Experience in
production support
, handling tickets, and monitoring ETL systems.
Strong SQL skills with experience in querying large datasets.
Familiarity with data warehousing concepts and design (e.g., star schema, snowflake schema).
Experience with relational databases such as Oracle, SQL Server, or PostgreSQL.
Knowledge of cloud platforms such as AWS, Azure, or GCP is a plus.

Preferred Qualifications:

BS degree in Computer Science or Engineering or equivalent experience

Roles and Responsibilities

Roles and Responsibilities:

Design, develop, and maintain robust ETL pipelines using
Informatica
.
Work with data architects and business stakeholders to understand data requirements and translate them into technical solutions.
Integrate data from various sources including relational databases, flat files, APIs, and cloud-based systems.
Optimize and troubleshoot existing Informatica workflows for performance and reliability.
Monitor ETL workflows and proactively address failures, performance issues, and data anomalies.
Respond to and resolve support tickets related to data loads, ETL job failures, and data discrepancies.
Provide support for production data pipelines and jobs
Ensure data quality and consistency across different systems and pipelines.
Implement data validation, error handling, and auditing mechanisms within ETL processes.
Collaborate with data analysts, data scientists, and other engineers to ensure a consistent and accurate data platform.
Maintain documentation of ETL processes, data flows, and technical designs.
Monitor daily data loads and resolve any ETL failures or data quality issues.

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