Senior AWS Data Engineer at Weekday AI
, , India -
Full Time


Start Date

Immediate

Expiry Date

25 Jan, 26

Salary

3500000.0

Posted On

27 Oct, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Amazon Redshift, Snowflake, MSSQL, AWS Data Services, ETL/ELT Pipeline Development, SQL & Query Optimization, Schema Design & Data Modeling, Data Governance & Observability

Industry

technology;Information and Internet

Description
This role is for one of the Weekday's clients Salary range: Rs 3000000 - Rs 3500000 (ie INR 30-35 LPA) Min Experience: 8 years Location: Remote (India) JobType: full-time We’re looking for an experienced Senior AWS Data Engineer to design, build, and maintain the systems that power data-driven decision-making. You’ll architect and optimize scalable data pipelines and databases across platforms such as Amazon Redshift, Snowflake, and MSSQL, ensuring reliability, accessibility, and performance at scale. If you’re passionate about solving complex data challenges, fine-tuning performance, and becoming a trusted data expert within a collaborative engineering environment — this role is for you. What You’ll Do Design and maintain scalable, efficient, and well-structured schemas across Redshift, Snowflake, and MSSQL. Architect and optimize complex queries, stored procedures, indexing strategies, and partitioning for large datasets. Build, monitor, and manage high-performance data pipelines to ensure timely and accurate data delivery. Own and maintain data refresh SLAs, ensuring availability, consistency, and reliability across all environments. Collaborate with engineering, analytics, and DevOps teams to align data models with product and reporting requirements. Proactively identify and resolve performance bottlenecks, slow queries, and data inconsistencies. Implement and manage schema migration and versioning workflows for seamless database changes. Define, enforce, and evangelize best practices for data security, governance, and observability. What You’ll Bring 8+ years of experience in data engineering or backend systems development. 4+ years of hands-on experience with AWS data stack — particularly Amazon Redshift and Snowflake — including schema design and performance tuning. Proven experience designing and maintaining ETL/ELT pipelines that ensure data freshness, quality, and reliability. Strong command of SQL, T-SQL, and query optimization, including indexing, partitioning, and relational modeling. Experience leading or owning database architecture initiatives within a development team. Familiarity with Git/Bitbucket and CI/CD processes for version control and deployment. Strong analytical and problem-solving mindset with a proactive approach to identifying and mitigating data risks. Ability to translate business and product requirements into scalable data solutions in collaboration with cross-functional teams. Experience writing robust scripts, functions, and stored procedures to automate data workflows. Hands-on experience in diagnosing, troubleshooting, and resolving data-related issues to ensure smooth operations. Key Skills Amazon Redshift, Snowflake, MSSQL AWS Data Services (Glue, Lambda, S3, etc.) ETL/ELT Pipeline Development SQL & Query Optimization Schema Design & Data Modeling Data Governance & Observability
Responsibilities
Design, build, and maintain systems for data-driven decision-making. Architect and optimize scalable data pipelines and databases across platforms such as Amazon Redshift, Snowflake, and MSSQL.
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