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Weekday AI (YC W21)
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Data Engineer

Data Engineer

Weekday AI (YC W21)

5 years

0 Lacs

delhi india

Posted:2 days ago| Platform:

Apply

Skills Required

data analytics aws pipeline power stack development design support reporting learning etl integration databricks pyspark consistency efficiency management redshift reliability processing automation orchestration automate airflow governance checks monitoring troubleshooting optimization analyze sql storage architecture scalability collaboration documentation flow engineering workflow tuning analysis communication

Work Mode

On-site

Job Type

Full Time

Job Description

This role is for one of Weekday's clientsMin Experience: 5 yearsLocation: Delhi NCRJobType: full-time

Requirements

We are seeking a highly skilled and motivated

Data Engineer

to join our growing data and analytics team. The ideal candidate will bring strong expertise in

SQL

AWS cloud services

, and

data pipeline development

to build and maintain scalable, reliable, and efficient data infrastructure. You will play a key role in designing and optimizing data workflows that power critical business insights and decision-making across the organization.This position is perfect for an individual who thrives in fast-paced, data-driven environments and has a strong command of modern

AWS data stack tools

such as

S3

Glue

Kinesis

Redshift

, and

Databricks

Key Responsibilities

Data Pipeline Development: Design, build, and maintain robust, scalable, and high-performance data pipelines to support analytics, reporting, and machine learning initiatives. Implement ETL/ELT processes for structured and unstructured data from multiple sources into centralized data lakes or warehouses.
Data Integration & Transformation: Utilize AWS Glue, Databricks, and PySpark to transform, clean, and enrich large-scale datasets ensuring consistency and quality. Optimize data transformations and queries for performance and cost efficiency.
Data Lake & Warehouse Management: Architect, manage, and monitor data lakes on S3 and data warehouses on Redshift, ensuring high data availability and reliability. Develop solutions that support both real-time streaming and batch data processing using AWS Kinesis and related services.
Automation & Orchestration: Build and automate workflows using Airflow, Step Functions, or equivalent orchestration tools to streamline data movement and reduce manual intervention.
Data Quality & Governance: Ensure data accuracy, completeness, and consistency across systems through validation checks, monitoring, and proactive troubleshooting. Collaborate with data analysts and business teams to understand data needs and provide reliable, timely datasets.
Performance Optimization: Continuously analyze and optimize SQL queries, data pipelines, and storage architecture to improve efficiency, scalability, and performance.
Collaboration & Documentation: Work closely with data scientists, analysts, and business stakeholders to deliver scalable data solutions that support business objectives. Maintain detailed technical documentation, data flow diagrams, and process manuals for ongoing support and scalability.

Key Skills And Requirements

Experience: Minimum 5 years of hands-on experience in data engineering with strong exposure to AWS-based data ecosystems.
Technical Expertise:

Proficiency in SQL, AWS Glue, Kinesis, Redshift, S3, Databricks, and PySpark.
Experience in Data Lake design, ETL pipeline orchestration, and workflow automation.
Familiarity with Airflow, Step Functions, or similar orchestration frameworks.

Data Management: Strong understanding of data modeling, performance tuning, and data quality management.
Analytical Skills: Ability to perform detailed data analysis and identify opportunities for process improvement.
Cloud Expertise: Deep understanding of AWS architectures, cost optimization, and infrastructure best practices.
Soft Skills: Excellent communication, problem-solving, and collaboration skills in cross-functional environments.
Work Mode: Ability to work onsite 2 days/week from CyberHub, Gurugram

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Data Engineer

Experience & Salary

Skills Required

Work Mode

Job Type

Job Description

Requirements

Data Engineer

SQL

AWS cloud services

data pipeline development

AWS data stack tools

S3

Glue

Kinesis

Redshift

Databricks

Key Responsibilities

Key Skills And Requirements

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