Data Engineer-ETL/Snowflake (S04)

About US:

Systango Technologies Limited (NSE: SYSTANGO) is a digital engineering company that offers enterprise-class IT and product engineering services to different size organizations. At Systango, we have a culture of efficiency - we use the best-in-breed technologies to commit quality at speed and world-class support to address critical business challenges. We leverage Gen AI, AI/Machine Learning and Blockchain to unlock the next stage of digitalization for traditional businesses. Our handpicked team is adept at web & enterprise development, mobile apps, QA and DevOps. Sila, Cuentas, Youtility, Porsche, MGM Grand, Deloitte, Grindr, and Tawk.to are some of the top clients that have entrusted us to enhance their digital capabilities and build disruptive innovations. We believe in making the impossible, Possible and we do it literally.

We are looking for an experienced Data Engineer with strong expertise in ETL, Snowflake, and Databricks to design, build, and maintain scalable data pipelines and data solutions.

Key Responsibilities

• Design and develop robust ETL/ELT pipelines for large-scale data processing.
• Work extensively with Snowflake for data warehousing, transformation, optimization, and performance tuning.
• Build and manage data pipelines using Databricks and PySpark.
• Work with SQL, Python, data modelling, and cloud-based data platforms.
• Integrate data from multiple sources and ensure data quality, reliability, and scalability.
• Collaborate with product, engineering, and business teams to understand requirements and deliver effective data solutions.
• Take ownership of projects and independently drive them from requirement understanding to delivery.

Required Skills

• 8–10 years of experience in Data Engineering.
• Strong hands-on experience with ETL/ELT and Snowflake.
• Good experience with Databricks / PySpark.
• Strong SQL and Python skills.
• Good understanding of data warehousing, data modelling, and data pipelines.
• Snowflake certification is preferred.
• Strong communication and stakeholder-management skills.
• Ability to understand requirements, ask the right questions, and independently drive projects end-to-end.

Required Skills

Data Engineering

• Strong experience designing and building production-grade ETL/ELT pipelines.
• Experience with batch and streaming data processing.
• Good understanding of data modeling, warehouse/lakehouse architecture, and performance optimization.

Programming

• Strong Python programming skills.
• Advanced SQL.
• Hands-on experience with Apache Spark (PySpark preferred).
• Scala is a plus.

Data Platforms & Warehouses

• Experience with one or more cloud ecosystems and modern analytical platforms:
• AWS, Azure, or GCP
• Snowflake, Databricks, Amazon Redshift, Google BigQuery, or Azure Synapse
• Lakehouse technologies such as Delta Lake, Apache Iceberg, or Apache Hudi

Data Processing & Orchestration

• Apache Spark
• Apache Kafka or AWS Kinesis
• Airflow, Dagster, or Prefect
• dbt

Databases

• PostgreSQL, MySQL, or other relational databases
• Experience with NoSQL databases such as MongoDB is a plus.

DevOps

• Docker and Kubernetes
• Infrastructure as Code (Terraform preferred)
• CI/CD for data engineering workflows