AWS Data Engineer

Company Description

Sufalam Technologies, based in Ahmedabad, India, is an IT services and solutions company known for integrating and optimizing complex technologies and data to enhance business results. We bring together real-world business experience with deep technology expertise, service delivery tools, and proven methodologies to help clients achieve their strategic objectives. Our services include Custom Application Development, Web Application and Development, BPO, and much more. Our expertise in different vertical industry domains and a wide range of software tools has ensured a consistent track record of delivering top-notch IT Services globally.

Role Description

This is a full-time on-site role for an AWS Data Engineer located in Ahmedabad. The AWS Data Engineer will be responsible for designing and implementing data engineering solutions, developing data models, managing Extract, Transform, Load (ETL) processes, and ensuring the efficient operation of data warehousing solutions. Additionally, the engineer will contribute to data analytics activities to support business decision-making and strategic goals.

Key Responsibilities

● Design and implement scalable and secure ETL/ELT pipelines on AWS for processing financial data.

● Build automated data reconciliation systems to ensure data integrity and accuracy across multiple financial sources (e.g., bank statements, internal ledgers, ERP, payment gateways).

● Collaborate closely with Finance, Data Science, and Product teams to understand reconciliation needs and ensure timely data delivery.

● Implement monitoring and alerting for pipeline health and data quality.

● Maintain detailed documentation on data flows, data models, and reconciliation logic.

● Ensure compliance with financial data handling and audit standards.

Must-Have Skills

● 5-6 years of experience in data engineering, with a strong focus on AWS data services.

● Hands-on experience with:

○ AWS Glue, Lambda, S3, Redshift, Athena, Step Functions

○ AWS Lake Formation and IAM for secure data governance

● Solid understanding of data reconciliation processes in the finance domain (e.g., matching transactions, resolving mismatches, variance analysis).

● Strong SQL skills and experience with data warehousing and data lakes.

● Experience with Python or PySpark for data transformation.

• ● Knowledge of financial accounting principles or experience working with financial datasets (AR, AP, General Ledger, etc.).