Data Engineer - Bangalore
Bengaluru, Karnataka, India
- Remote-first
- Website
- @weekdayworks 𝕏
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Weekday
At Weekday, we help companies hire engineers who are vouched by other software engineers. We are enabling engineers to earn passive income by leveraging & monetizing the unused information in their head about the best people they have worked...This role is for one of Weekday's clients
Salary range: Rs 3500000 - Rs 6000000 (ie INR 35-60 LPA)
Min Experience: 9 years
Location: Bengaluru
JobType: full-time
Requirements
About the Role:
We are seeking a highly experienced and innovative Senior Data Engineer to join our growing data team. As a Data Engineer, you will be responsible for designing, developing, and maintaining robust data pipelines and scalable architectures that support our business intelligence, analytics, and data-driven decision-making initiatives. You will work closely with data scientists, analysts, product managers, and other stakeholders to ensure that our data infrastructure is efficient, reliable, and aligned with business goals.
This is a strategic role ideal for someone who thrives in a fast-paced environment, has deep experience in data engineering best practices, and is passionate about leveraging data to drive impact at scale.
Key Responsibilities:
- Data Architecture & Pipeline Development:
- Design and build highly scalable, efficient, and secure data pipelines for batch and real-time data processing.
- Develop and maintain ETL/ELT processes to extract, transform, and load data from multiple sources into data warehouses and data lakes.
- Data Modeling & Warehousing:
- Create and maintain optimized data models that support advanced analytics and reporting.
- Design and implement data warehousing solutions using modern data storage technologies.
- Data Quality & Governance:
- Ensure high levels of data availability, quality, and integrity through the implementation of robust data validation, monitoring, and governance practices.
- Partner with compliance and data governance teams to enforce data security and privacy policies.
- Collaboration & Cross-functional Partnership:
- Work closely with data scientists, analysts, and business teams to understand data requirements and provide reliable data solutions.
- Collaborate with DevOps and infrastructure teams to automate deployment and manage cloud-based data environments.
- Tooling & Performance Optimization:
- Implement monitoring tools and optimize performance of data pipelines and database systems.
- Stay updated with the latest trends in data engineering, and evaluate new tools and technologies for adoption.
Required Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Information Systems, Engineering, or a related field.
- 9+ years of hands-on experience in Data Engineering, with a deep understanding of scalable data pipeline architecture.
- Proficient in at least one programming language such as Python, Java, or Scala.
- Strong experience with ETL/ELT frameworks, data orchestration tools (e.g., Apache Airflow, DBT), and workflow management.
- Solid experience working with cloud data platforms (e.g., AWS, Azure, GCP) and data storage solutions (e.g., Snowflake, Redshift, BigQuery).
- Expertise in SQL and data modeling for both OLAP and OLTP systems.
- Familiarity with distributed systems, streaming technologies (Kafka, Spark), and containerization (Docker, Kubernetes) is a plus.
Preferred Skills:
- Experience in a fast-paced startup or enterprise data team.
- Exposure to big data technologies and real-time data processing.
- Strong analytical thinking and problem-solving skills.
- Excellent communication and project management abilities.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow Architecture AWS Azure Big Data BigQuery Business Intelligence Computer Science Data governance Data pipelines Data quality Data Warehousing dbt DevOps Distributed Systems Docker ELT Engineering ETL GCP Java Kafka Kubernetes OLAP Pipelines Privacy Python Redshift Scala Security Snowflake Spark SQL Streaming
Perks/benefits: Startup environment
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