Etl Analyst (ETL/SQL/ Snowflake)

Tech Mahindra; Dadri, Pune District; On-site; INR 600,000 - 1,200,000; Full time

Job summary

Tech Mahindra is seeking a motivated L1 Data Engineer to support ingestion, monitoring, validation, and operational activities in a healthcare analytics environment. You will work with SQL, Snowflake, and AWS-based data pipelines to ensure timely production issue resolution and data quality.

You will engage in data architecture understanding across Landing to L3 layers, collaborate with senior engineers, and gain knowledge of healthcare datasets including sales, patient, provider, product, and

Qualifications

• Strong SQL querying and data validation required.
• 0
• Hands-on Snowflake experience is essential.
• Understanding of ETL/data pipeline concepts.
• Basic scripting in Python preferred.
• Familiarity with AWS services (Glue, S3, Lambda, Step Functions).
• Knowledge of data warehousing concepts.
• Healthcare/pharmaceutical data domain awareness is a plus.
• Excellent problem-solving and communication skills.

Responsibilities

• Monitor and execute Snowflake and AWS-based data pipelines.
• Support daily data load activities and validate pipeline execution results.
• Ensure successful ingestion of source data into Snowflake layers.
• Review pipeline run history, task statuses, and execution logs.
• Write and execute SQL queries for data analysis, validation, and troubleshooting.
• Perform data reconciliation and quality checks across source and target systems.
• Support root cause analysis for data discrepancies and load failures.
• Validate fact and dimension table outputs against business requirements.
• Execute and monitor Snowflake tasks, stored procedures, and workflows.
• Support incremental and full-load processes.
• Investigate and resolve Snowflake pipeline failures and data quality issues.
• Assist in performance monitoring and basic query optimization.
• Develop an understanding of end-to-end data flow across Landing, Raw, L1, L2, and L3 layers.
• Understand fact/dimension data models and business KPI generation processes.
• Work closely with senior engineers to support enhancements and operational activities.
• Gain knowledge of healthcare and pharmaceutical data domains.
• Understand healthcare datasets such as sales, patient, provider, product, and market data.
• Collaborate with business stakeholders to understand reporting and analytical needs.
• Perform Level-1 investigation of production incidents.
• Analyze logs, data loads, workflow failures, and validation errors.
• Escalate complex technical issues with sufficient troubleshooting details.
• Maintain operational documentation and incident records.
• Prepare operational runbooks and troubleshooting guides.
• Provide regular status updates on pipeline executions and issue resolutions.
• Participate in KT sessions, stand-ups, and operational review meetings.

Skills

SQL querying

Data validation

Python scripting

Analytical thinking

Problem solving

Communication

Tools

Snowflake

AWS (Glue, S3, Lambda, Step Functions)

ETL/Data pipelines tooling

Job description

Role Summary

We are seeking a motivated L1 Data Engineer to support data ingestion, pipeline monitoring, data validation, and operational activities within a healthcare analytics environment. The role involves working with SQL, Snowflake, AWS-based data pipelines, and healthcare datasets while ensuring timely resolution of production issues and maintaining data quality.

Key Responsibilities

Data Pipeline Operations

• Monitor and execute Snowflake and AWS-based data pipelines.
• Support daily data load activities and validate pipeline execution results.
• Ensure successful ingestion of source data into Snowflake layers.
• Review pipeline run history, task statuses, and execution logs.

SQL Development & Data Validation

• Write and execute SQL queries for data analysis, validation, and troubleshooting.
• Perform data reconciliation and quality checks across source and target systems.
• Support root cause analysis for data discrepancies and load failures.
• Validate fact and dimension table outputs against business requirements.

Snowflake Administration & Support

• Execute and monitor Snowflake tasks, stored procedures, and workflows.
• Support incremental and full-load processes.
• Investigate and resolve Snowflake pipeline failures and data quality issues.
• Assist in performance monitoring and basic query optimization.

Data Architecture Understanding

• Develop an understanding of end-to-end data flow across Landing, Raw, L1, L2, and L3 layers.
• Understand fact/dimension data models and business KPI generation processes.
• Work closely with senior engineers to support enhancements and operational activities.

Healthcare Business Knowledge

• Gain knowledge of healthcare and pharmaceutical data domains.
• Understand healthcare datasets such as sales, patient, provider, product, and market data.
• Collaborate with business stakeholders to understand reporting and analytical needs.

Incident Management & Troubleshooting

• Perform Level-1 investigation of production incidents.
• Analyze logs, data loads, workflow failures, and validation errors.
• Escalate complex technical issues with sufficient troubleshooting details.
• Maintain operational documentation and incident records.

Documentation & Communication

• Prepare operational runbooks and troubleshooting guides.
• Provide regular status updates on pipeline executions and issue resolutions.
• Participate in KT sessions, stand-ups, and operational review meetings.

Required Skills

Technical Skills

• Strong SQL querying and data validation skills.
• Hands-on experience with Snowflake.
• Understanding of ETL/Data Pipeline concepts.
• Basic knowledge of AWS services (Glue, S3, Lambda, Step Functions is preferred).
• Familiarity with data warehousing concepts.
• Basic scripting knowledge (Python preferred).

Functional Skills

• Understanding of healthcare/pharmaceutical business processes is desirable.
• Analytical and problem-solving mindset.
• Strong communication and documentation skills.
• Ability to work in a production support environment.

Experience

• 1-3 years of experience in Data Engineering, Data Operations, or Data Support.
• Freshers with strong SQL and data engineering fundamentals may also be considered.