Lead Data Engineer

We are looking for a Lead Data Engineer with 7-10 years of experience to design and scale our data platform. You will own data architecture across ingestion, streaming, storage, processing, analytics, security, and reliability in a high-growth fintech environment.

Responsibilities:

• Design and scale end-to-end data platforms supporting batch and real-time workloads.
• Build scalable ETL/ELT and CDC pipelines using Kafka, Debezium, Spark/Flink, and Airflow.
• Architect data lakes/lakehouses using S3 Parquet, Iceberg, and Delta Lake.
• Design and optimize ClickHouse/Redshift/BigQuery architectures, including schema design, aggregation, sharding, and replication.
• Build multi-tenant data architectures with strong isolation, security, and compliance.
• Drive data observability, lineage, quality, and disaster recovery across critical pipelines.
• Define infrastructure using Terraform and drive compute/storage and cost optimization.
• Partner with platform and security teams on AWS, VPC, IAM, encryption, and data security.
• Mentor engineers and establish data architecture standards and best practices.

Requirements:

• 7-10 years of strong hands-on data engineering experience with architectural ownership.
• Strong expertise in distributed systems, Spark, Flink, and Kafka.
• Hands-on experience with AWS data services: S3 Glue, RDS, MSK, Redshift, DMS, and Athena.
• Strong experience with ClickHouse, BigQuery, Redshift, or Snowflake.
• Expertise in data modelling: Star Schema, Data Vault 2.0 and OBT.
• Strong experience with streaming, CDC, dbt, Python, SQL, and Airflow.
• Hands-on experience with Terraform/CloudFormation.
• Strong understanding of IAM, encryption, VPC, multi-tenancy, and data security.
• Experience building data platforms from the ground up and at significant scale.