Data Engineer II

Responsibilities:

• Build and automate large-scale, high-performance data pipelines (batch and streaming).
• Define and own Sources of Truth (SOT) and dataset design used across multiple teams.
• Streamline ingestion and processing of raw event sources into authoritative event logs.
• Lead data engineering projects, ensuring pipelines are reliable, efficient, testable, and maintainable.
• Design and optimise data models for analytics, reporting, and downstream product use cases.
• Build systems to monitor data quality, data loss, SLAs, and reliability of Tier-1 and Tier-2 datasets.
• Devise strategies to detect, reconcile, and compensate for data loss across multiple sources.
• Evangelise high-quality software engineering practices for data infrastructure at scale.
• Collaborate with Data Science, Analytics, Product, and Engineering teams to align on data architecture.
• Contribute to shared data tooling, frameworks, and standards to improve developer productivity.

Requirements:

• 3-5+ years of relevant Data Engineering or Software Engineering experience.
• Bachelor's or Master's degree in Computer Science, Engineering, or equivalent practical experience.
• Strong experience working with large-scale datasets (terabyte to petabyte-scale).
• Solid background in distributed systems design and operation.
• Excellent SQL skills (mandatory); experience with complex analytical queries.
• Solid understanding of data modelling (star/snowflake schemas, fact and dimension tables).
• Hands-on experience with Spark and data processing frameworks.
• Proficiency in one or more programming languages: Java, Scala, or Python.
• Well-versed with tools of one of the Cloud vendors, i. e., AWS, GCP, Azure.
• Experience with ETL frameworks, data pipelines, data lakes, and data modelling fundamentals.
• Strong understanding of monitoring, logging, and observability for data systems.
• Ability to work across teams to define overarching data architecture and influence best practices.
• Strong problem-solving skills and attention to data correctness and reliability.
• Excellent written and verbal communication skills.

Must Have:

• Strong understanding of monitoring, logging, and observability for data systems.
• Experience with real-time / streaming data (Kafka, Flink, Beam).
• Familiarity with Hadoop / HDFS ecosystems.
• Experience building or integrating with backend services.
• Exposure to cloud platforms (AWS, GCP, or Azure) includes optimisation (pipelines, cost).
• Exposure to Snowflake, SQL at scale, and modern analytics engineering.
• Exposure to designing building secured data systems using RBAC, CBAC for audit and compliance.

Why Explore a Career at Unloq

• Be a part of the team that solves the most burning problem - Achieving growth.
• Opportunity to join an early-stage team, giving you a lot of ownership and accelerated career growth
• Intense brainstorming and whiteboarding on interesting problems and innovation are guaranteed.
• Work directly with founders and align with the vision of the company.
• Competitive ESOPs are aligned with the company's long-term vision.