Data Lake Architect at Croyant Technologies Pvt Ltd

Data Lake Architect

Role Overview

We are seeking a highly skilled Data Lake Architect with over 7 years of experience in designing and implementing large-scale data lake and analytics solutions. The ideal candidate will provide end-to-end ownership of the data lake architecture, ensuring scalability, security, and performance across complex enterprise environments. The role involves working closely with business stakeholders, data engineers, DevOps teams, and security architects to deliver innovative and efficient data-driven platforms.

Key Responsibilities

Architecture & Design

Define and implement enterprise-grade data lake architecture aligned with business needs.

Design frameworks for ingestion, storage, transformation, cataloging, and governance of structured, semi-structured, and unstructured data.

Create scalable and secure solutions leveraging cloud-native and on-prem platforms.

Data Integration & Engineering

Oversee real-time and batch data ingestion pipelines (ETL/ELT).

Enable seamless integration with analytics, AI/ML platforms, and BI tools.

Standardize metadata management and data lineage tracking.

Security & Governance

Implement robust data governance frameworks (role-based access, compliance with GDPR/CCPA, data masking, encryption).

Collaborate with cybersecurity teams on IAM, PKI, Zero Trust, and secrets management.

Performance & Optimization

Optimize storage and compute for performance and cost efficiency.

Establish monitoring, logging, and performance tuning best practices.

Leadership & Collaboration

Guide to data engineering and DevOps teams in implementing best practices.

Provide architectural thought leadership and mentor junior team members.

Partner with business leaders to translate requirements into scalable solutions.

Required Skills & Experience

Technical Expertise

7+ years of experience in data engineering, data platforms, or big data solutions.

Strong hands-on expertise with Data Lake technologies: Hadoop, Spark, Hive, Presto, Delta Lake, Apache Iceberg, Kafka, NiFi, or equivalent.

Cloud platforms: AWS (S3, Glue, EMR, Redshift, Lake Formation), Azure (ADLS, Synapse, Data Factory), or GCP (BigQuery, Dataflow).

Proficiency in data modeling, ETL/ELT pipelines, and stream processing.

Familiarity with DevOps tools (Kubernetes, Docker, CI/CD, Terraform) and automation.

Security & Compliance

Knowledge of encryption, IAM, key management (Thales, CyberArk, AWS KMS).

Understanding of regulatory frameworks (GDPR, HIPAA, NCA-CCC, etc.).

Soft Skills

Strong problem-solving, analytical thinking, and communication skills.

Proven track record of collaborating with cross-functional stakeholders.

Ability to mentor and build high-performing engineering teams.

Education & Certifications

B.Tech / B.E or MTech or MCA

Preferred certifications:

AWS Certified Data Analytics – Specialty / Azure Data Engineer Associate / GCP Professional Data Engineer

TOGAF or equivalent architecture certification (nice to have).