Job highlights

- Build automated workflows for data ingestion,transformation,and delivery across batch and real-time environments
- 5+ years of experience in Data Engineering or related roles
- . Hands-on experience with distributed data processing frameworks such as Spark,Flink,or Kafka
- Experience working with time-series data platforms and large-scale data systems

Responsibilities
- Data Pipeline Engineering & Automation: Design and maintain scalable ETL/ELT pipelines for structured, semi-structured, unstructured, and time-series data.
- Build automated workflows for data ingestion, transformation, and delivery across batch and real-time environments.

Data Modeling & Platform Architecture:
- Develop scalable data models and contribute to data lake, lakehouse, and warehouse architecture to support analytics, AI/ML, and digital product needs.

Data Platforms & Technologies:
- Implement solutions using modern data tools and frameworks such as Kafka, Spark, Flink, PostgreSQL, ClickHouse, InfluxDB, or similar technologies.

Data Quality, Observability & Reliability:
- Establish validation, lineage tracking, monitoring, and alerting to ensure data quality, reliability, and performance.

API Integration & Data Connectivity:
- Build and maintain secure APIs and integrations to enable seamless data exchange across internal and external systems.

Security, Compliance & Lifecycle:
- Apply secure-by-design practices and support data governance, regulatory compliance, and lifecycle management.

Cross-Functional Collaboration:
- Work closely with Data Scientists, ML Engineers, Cloud Engineers, and Product Owners to deliver scalable data solutions.

Our requirements Must Have Skills & Experience:




- 5+ years of experience in Data Engineering or related roles.
- Strong programming skills in Python, SQL, or similar languages (Scala/Java is a plus).
- Hands-on experience with distributed data processing frameworks such as Spark, Flink, or Kafka.
- Experience working with time-series data platforms and large-scale data systems.
- Solid understanding of ETL/ELT design patterns and scalable data architectures.
- Experience with data modeling, data warehousing, or lakehouse concepts.
- Strong analytical and problem-solving skills.

Good to Have Skills & Experience:
- Experience with cloud data platforms or containerized environments.
- Exposure to real-time streaming architectures or event-driven systems.
- Familiarity with AI/ML data pipelines or feature engineering workflows.
- Knowledge of monitoring, observability, and data governance practices.
- Experience working with industrial, IoT, or digital monitoring platforms. analysis tools.

Soft Skills
- Strong problem-solving and analytical skills.
- Excellent communication and cross-functional collaboration skills.
- Proactive attitude and ability to work independently or in a team.
- Solid documentation and presentation skills.

Business Impact:
- Enables reliable, scalable data delivery for analytics and digital products.
- Supports faster development of data-driven services and intelligent solutions.
- Improves operational efficiency through high-quality data engineering practices.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Data Engineer - Digital Services M/F (Bengaluru)
🏢 KK Wind Solutions
📍 Bengaluru