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Data Engineer

Fam
Bengaluru, IND
Full-time
Mid-Senior
Onsite
Discovered 1 weeks ago
Data engineeringPythonPySparkSQLAWSInfrastructure as code
Free

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About Fam

Fam, previously FamPay, is an Indian payments app offering UPI and FamCard services for users above age 11.

The company is building a fintech lifestyle brand combining money, identity, and everyday experiences.

About the Role

Fam is hiring a Data Engineer II, also described as an SDE-2, for its data team.

The role focuses on building a high-performance, scalable data lakehouse, moving toward sub-minute data latency and unified batch and streaming compute.

The position is engineering-heavy and includes complex CDC flows, distributed query optimization, and AI-assisted development.

Must-Have Requirements

  • 3–5 years of data engineering experience with distributed systems and cloud-native architectures.
  • Expert-level Python or PySpark and SQL skills.
  • Hands-on AWS experience with S3, EKS, and MSK, together with infrastructure as code.
  • Experience with Airflow or Temporal for complex workflow management.
  • Proficiency using Claude, Codex, Copilot, or similar AI tools to write, test, and document code.
  • Ability to explain trade-offs between storage formats and processing frameworks.
  • Ability to prepare technical requirements documents, participate in design reviews, and drive technical initiatives.
  • Hands-on OLAP modeling using fact, dimension, cumulative, SCD, and OBT pattern tables.
  • Ability to lead technically, contribute new ideas, and work with product and key stakeholders.

Preferred Experience

  • High-throughput real-time CDC ingestion from relational databases using Debezium or PeerDB.
  • Lakehouse table formats including Iceberg, Delta, or Hudi.
  • Batch and streaming workloads using PySpark and Flink.
  • AWS data workloads using EMR, EKS, MSK, and S3, automated with GitLab or GitHub Actions.
  • Query and BI systems including Trino, ClickHouse, Metabase, Superset, and Power BI.

Technical Responsibilities

  • Develop the data lakehouse and unified batch and streaming compute capabilities.
  • Manage CDC flows and optimize distributed query engines.
  • Drive technical initiatives, prepare technical requirements documents, and participate in design reviews.
  • Design OLAP domain models and data marts using fact, dimension, SCD, and OBT patterns.
  • Lead the team technically and contribute ideas to grow the data engineering charter.
  • Partner with product and stakeholders to improve business workflows through data and analytics.
  • Build and operate ingestion, orchestration, data quality, governance, infrastructure, and analytics-serving systems.

Technology Stack

  • OLake and PeerDB support near-real-time synchronization, with Debezium and Kafka for CDC-heavy use cases.
  • Apache Iceberg with S3 and AWS Glue Catalog supports the lakehouse storage layer.
  • PySpark on EMR or EKS supports batch and streaming workloads, with Flink and Spark Structured Streaming fundamentals.
  • MSK and Kafka support event-driven ingestion, CDC propagation, replay, backfills, and monitoring.
  • Trino, ClickHouse, and BigQuery support lakehouse analytics, operational dashboards, and real-time serving.
  • Airflow supports scheduled pipelines, data-quality checks, reconciliation, backfills, and SLA-driven jobs; Temporal supports durable workflows.
  • AWS, Kubernetes, Terraform, GitLab or GitHub Actions, Grafana, and CloudWatch support infrastructure and operations.
  • Metabase, Superset, Tableau, and Power BI support business dashboards and stakeholder-facing analytics.

Benefits and Perks

  • Relocation assistance, free office meals, and a generous leave policy.
  • Salary advance and loan policies, quarterly rewards, recognition programs, and referral incentives.
  • Access to gadgets and tools, comprehensive health insurance, mental health support, and tax-benefit options.
  • Retirement benefits including provident fund contributions, leave encashment, and gratuity.

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