Data Engineer

Monk's Hill Ventures; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Monk's Hill Ventures is seeking a Data Engineer to build the future of digital identity at VIDA. This role involves working across the stack, from data pipelines to infrastructure, and leading initiatives in streaming and real-time fraud detection.

Candidates should have 5+ years of experience in data engineering, solid expertise in AWS, and familiarity with tools like Scala Spark and Terraform. The position offers an opportunity to work in a fast-paced environment while collaborating with engineering and data science teams.

Qualifications

• 5+ years of relevant experience in data engineering and/or distributed systems.
• Hands-on experience with data pipelines using distributed frameworks like Spark.
• Familiarity with AWS services for data, such as S3, Lambda, or Redshift.

Responsibilities

• Build and expose the data lake/lakehouse for better decision making.
• Design and evolve a data platform for querying and shipping features.
• Develop scalable batch and streaming pipelines for trusted datasets.

Skills

Data engineering

Distributed systems

Building data pipelines

SQL

AWS

Terraform

Workflow orchestration

Tools

Scala Spark

dbt

Terraform

Job description

Data Engineer

Location: Bengaluru, Karnataka

Work Type: Full Time

At VIDA we’re building the future of digital identity.

As a Data Engineer, you’ll work across the stack—from platform and infrastructure to data pipelines and end-user tooling. You’ll help modernize our batch ETLs and lead our push into streaming and real-time fraud detection. We run on AWS and make extensive use of Scala Spark, dbt, and Terraform.

Responsibilities

• Build and expose the data lake/lakehouse so teams can understand business and product performance and make better decisions.
• Design and evolve a data platform that enables scientists and analysts to query, model, and ship features and product metrics.
• Develop scalable and reliable batch and streaming pipelines that ingest from varied sources and land trusted datasets.
• Maintain and fix existing ETLs, improving reliability, observability, and cost while planning safe backfills and replays.
• Model curated layers and maintain transformation logic (e.g., dbt), including testing, documentation, and data quality.
• Build with Infrastructure as Code (e.g., Terraform) and contribute to CI/CD and deployment practices.
• Partner with Engineering and Data Science to deliver low-latency signals and features for real-time decisioning.
• Contribute to internal tools, reusable components, and simple dashboards that unblock self-service.

Requirements

• Solid engineering foundation with 5+ years of relevant experience in data engineering and/or distributed systems.
• Hands‑on work building data pipelines (batch and/or streaming) using at least one distributed framework (e.g., Spark, Kafka, Flink).
• Comfortable with SQL and a transformation framework (e.g., dbt or similar).
• Familiarity with AWS services for data (any mix of S3, EMR/Glue, Kinesis/MSK, Lambda, Redshift/Athena) or equivalent cloud experience.
• Exposure to workflow orchestration (e.g., Airflow).
• Experience using Terraform (or similar IaC) to manage data/platform resources.
• Ownership mindset, focus on reliability, and enjoyment of collaborating in a fast-moving environment.

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