Senior Data Engineer

Arcana; Bengaluru Urban; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Arcana in Bengaluru, India, seeks a seasoned Senior Data Engineer to design and optimize real-time data ingestion and processing systems. You will own and scale production data pipelines spanning ingestion to consumption within a robust big data architecture using PySpark.

The role requires deep Python, Airflow, SQL expertise and strong cloud platform knowledge. You will collaborate with a high-caliber data engineering team to deliver reliable, high-performance data solutions.

Qualifications

• Bachelor's degree in CS or IT.
• 3–8 years of data engineering experience.
• Strong PySpark, ETL and data pipeline expertise.

Responsibilities

• Develop and implement real-time data ingestion and processing systems.
• Design, build, and operationalize large-scale enterprise data solutions and applications.
• Create and manage production data pipelines from ingestion to consumption within a big data architecture using PySpark.
• Leverage Python, Airflow, SQL, and cloud platforms to build robust solutions.
• Translate complex business challenges into scalable and efficient technical solutions.
• Collaborate with a high-performing data engineering team, owning the full lifecycle of solution implementation.

Skills

PySpark

Python

Airflow

SQL

Cloud platforms

ETL

Data warehousing

Git/GitHub

NoSQL databases

Big data

Education

Bachelor's degree in CS/IT

Tools

Hadoop/EMR/Hive/Sqoop

Cassandra/MongoDB/HBase

AWS EMR/Redshift/Kinesis

Job description

Join our dynamic team at the forefront of cutting-edge technology as we seek a seasoned Senior Data Engineer. Embark on a journey where your deep-rooted expertise in computer science fundamentals, alongside an intricate understanding of data structures, algorithms, and system design, becomes the cornerstone of innovative solutions. This pivotal role not only demands your proficiency in developing and elevating compute and I/O-intensive applications but also ensures their peak performance and unwavering reliability.

Responsibilities

• Develop and implement real-time data ingestion and processing systems.
• Design, build, and operationalize large-scale enterprise data solutions and applications.
• Create and manage production data pipelines, from ingestion to consumption, within a big data architecture using PySpark.
• Leverage expertise in Python, Airflow, SQL, and cloud platforms to build robust solutions (strong knowledge of these is essential).
• Translate complex business challenges into scalable and efficient technical solutions.
• Work collaboratively with a high-performing data engineering team, owning the full lifecycle of solution implementation.

Requirements

• Bachelor's Degree in Computer Science, Information Technology, or a similar discipline.
• 3 - 8 years of professional experience in data engineering or related fields.
• Proven experience with ETL processes, data integration, and handling large-scale datasets using PySpark.
• Strong understanding of data engineering concepts like ETL, near/real-time streaming, data structures, and workflow management.
• Experience with version control tools like Git/GitHub.
• Proficiency in SQL and Data Warehouse concepts.
• Experience working with SQL or NoSQL databases like Cassandra, MongoDB, or HBase.
• Knowledge of AWS technologies such as EMR, RedShift, Kinesis, Lambda, Glue, S3 IAM, CloudWatch, and big data tools like Hadoop/EMR, Hive, and Sqoop.