AWS Data Engineer

Facctum; Bengaluru; On-site; INR 1,500,000 - 2,800,000; Full time

Job summary

Facctum IT Solutions India Private Limited in Bengaluru is hiring an experienced AWS Data Engineer to lead a large-scale migration from MatillionETL to an AWS-native data platform.

You will design scalable pipelines using Apache Airflow, AWS Glue, Snowflake, and AWS Lambda, collaborate with stakeholders, and establish cloud data engineering best practices.

Qualifications

• Experience migrating ETL workloads to AWS-native architectures.
• Hands-on AWS data services including Airflow, Glue, Snowflake.
• Strong data modeling and warehousing knowledge.
• Experience with CI/CD for data engineering is a plus.

Responsibilities

• Develop modules to migrate Matillion jobs to AWS-native solutions.
• Design scalable data pipelines using AWS Glue and Airflow.
• Build data ingestion, transformation, and orchestration on AWS.
• Collaborate with data architects and engineers on migration needs.
• Optimize performance, cost, and scalability of data workflows.
• Implement data quality, monitoring, and governance practices.

Skills

Apache Airflow

AWS Glue

Snowflake

AWS Lambda

Step Functions

Git

Python

SQL

Spark

Matillion

Tools

Matillion

Job description

Facctum IT Solutions India Private Limited | Full time

Bangalore North, India

• Organisation Facctum IT Solutions India Private Limited
• Date Opened 09/01/2026
• Country India

Job Description

We are seeking an experienced AWS Data Engineer to lead and execute a large-scale migration from MatillionETL to a modern AWS-native data platform. The ideal candidate will possessdeep expertise in Apache Airflow, AWS Glue, AWS Lambda and Snowflake ,with a strong background in designing scalable data pipelines, cloud-based dataintegration, workflow orchestration, and data warehouse modernization.

The candidate will work closelywith business stakeholders, data architects, and engineering teams to migrateexisting ETL workloads, optimize data processing frameworks, and establish bestpractices for cloud-native data engineering.

Requirements

Key Responsibilities

• Develop modules/code for migration of existing Matillion jobs to AWS-native solutions.
• Participatein Requirements Analysis of existing data processing jobs.
• Design,develop, and promote scalable data pipelines using AWS Glue and ApacheAirflow (and other basic AWS Services) - must have.
• Buildrobust data ingestion, transformation, and orchestration frameworks onAWS.
• Createreusable and modular ETL/ELT components for enterprise data platforms.
• Datamodeling and warehousing concepts – must have
• Datamigration and modernization projects – good to have
• Implementdata quality, monitoring, alerting, security, governance, and compliancestandards.
• Collaboratewith data architects and business teams to understand migrationrequirements and translate them into technical solutions.
• Optimizedata processing performance, cost, and scalability across AWS services.
• Participatein CI/CD best practices and DevOps processes for data engineeringworkflows.
  

Mandatory Skills

Core Technologies

• ApacheAirflow (DAG development, workflow orchestration, scheduling,monitoring)
• AWSGlue (ETL jobs, Glue Studio, Crawlers, Data Catalog, Spark-basedtransformations)
• Snowflake (Data Warehousing, SnowSQL, Snowpipe, Streams & Tasks, PerformanceTuning)
• AWS Lambdaand Step Functions (preferred)
• Gitexperience (must-have)

Programming languages: Python,SQL, Spark (any 1 is must)

PySpark, Matillion, Shellscripting (good to have)

Experience Requirements

• 2+years of intensive hands-on experience with AWS data services.
• Provenexperience migrating ETL platforms such as Matillion (or other ETL tools like DataStage) to AWS-native architectures (Good to have).
• Strongexperience developing workflows in Apache Airflow.
• Extensiveexperience building and optimizing AWS Glue jobs.
• Hands-onexperience with Snowflake stored procedures (must-have), performance tuning (good-to-have).
• Strongunderstanding of cloud architecture, scalability, deployments.