Role & Responsibilities

- Design, develop, and maintain scalable ETL/ELT pipelines for processing large volumes of structured and unstructured data.
- Build and optimize cloud-based data platforms using AWS, Azure, or Google Cloud Platform (GCP).
- Develop data ingestion frameworks from various sources including databases, APIs, files, and streaming platforms.
- Implement data transformation and processing using Python, PySpark, SQL, and Spark.
- Design and maintain Data Lakes, Data Warehouses, and Lakehouse architectures.
- Develop and manage workflows using Apache Airflow, AWS Glue, Azure Data Factory, Cloud Composer, or similar orchestration tools.
- Work with Snowflake, Databricks, Redshift, BigQuery, Synapse Analytics, and other modern analytics platforms.
- Optimize data pipelines for performance, scalability, reliability, and cost efficiency.
- Implement data quality, governance, security, and monitoring solutions.
- Collaborate with business analysts, data scientists, architects, and stakeholders to deliver data-driven solutions.
- Develop real-time and batch processing solutions using Kafka, Kinesis, Pub/Sub, or Spark Streaming.
- Participate in code reviews, testing, deployment, and production support activities.

Preferred Candidate Profile

- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field.
- 3-8 years of experience in Data Engineering, Big Data,



or Cloud Data Platforms.
- Strong hands-on experience in Python, PySpark, SQL, and Spark.
- Experience with AWS services such as S3, Glue, Lambda, Redshift, Athena, EMR, and Step Functions.
- Experience with Azure services such as Azure Data Factory, Azure Databricks, ADLS, and Synapse Analytics.
- Experience with GCP services such as BigQuery, Dataflow, Dataproc, Cloud Storage, and Pub/Sub.
- Hands-on experience with Snowflake, Databricks, Delta Lake, or similar platforms.
- Knowledge of Data Modeling, Data Warehousing, ETL/ELT, and Lakehouse architectures.
- Experience with Apache Airflow, Kafka, DBT, Terraform, Git, and CI/CD pipelines.
- Strong analytical, problem-solving, and communication skills.
- Experience working in Agile/Scrum environments is preferred.

Perks and Advantages

- Competitive salary and performance-based incentives.
- Hybrid/Remote work opportunities.
- Health insurance and wellness benefits.
- Learning and certification support for AWS, Azure, GCP, Snowflake, and Databricks.
- Career growth opportunities and exposure to enterprise-scale projects.
- Employee referral rewards and recognition programs.
- Paid leaves, flexible work environment, and work-life balance initiatives.
- Access to cutting-edge cloud and big data technologies.
- Collaborative and innovation-driven work culture.

📌 Aws Data Engineer / Azure Data Engineer / GCP (Google Cloud Platform) (Bengaluru)
🏢 Aetherrise Solutions
📍 Bengaluru