Senior Data Engineer

Arcana; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

A leading tech company seeks a Senior Data Engineer to design and implement real-time data processing systems. Candidates should have 3-8 years of experience in data engineering, strong skills in Python and SQL, and a Bachelor's degree in Computer Science or related fields. This full-time role involves developing robust data solutions and managing production pipelines. Experience with AWS technologies and data integration is essential for success in this dynamic position.

Qualifications

• 3-8 years of professional experience in data engineering or related fields.
• Proven experience with ETL processes and handling large-scale datasets using PySpark.
• Strong understanding of data engineering concepts and workflow management.

Responsibilities

• Develop and implement real-time data ingestion and processing systems.
• Design and operationalize large-scale enterprise data solutions.
• Manage production data pipelines in a big data architecture using PySpark.
• Translate complex business challenges into scalable technical solutions.

Skills

Python

SQL

ETL processes

Data integration

Data structures

Workflow management

PySpark

Cloud platforms

Version control tools

Education

Bachelor's Degree in Computer Science or Information Technology

Tools

AWS (EMR, RedShift, Kinesis, etc.)

Cassandra

MongoDB

HBase

Git/GitHub

Job description

Direct message the job poster from Arcana

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.

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Engineering and Information Technology

Industries

Software Development, Technology, Information and Internet, and Information Services

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