Data Architect I (Lead Data Quality Engineer (Cloud-Agnostic Data Engineering Expertise)

12 years

0 Lacs

Posted:2 days ago| Platform: Linkedin logo

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On-site

Job Type

Full Time

Job Description

Summary

Role description

We are looking for an experienced

Lead Data Quality Engineer

with a strong background in

data engineering

to drive enterprise-wide data quality and reliability initiatives. This role will focus on building and scaling

data quality frameworks, validation processes, and performance testing

across modern,

cloud-agnostic data platforms

. The ideal candidate is a hands-on technologist who thrives on solving complex data challenges, ensuring trustworthy and high-performing data pipelines, and collaborating across teams to uphold enterprise data standards.

Key Responsibilities

Data Quality & Performance Engineering (Primary Focus)

  • Define, implement, and enhance data quality frameworks, validation rules, and monitoring systems for data pipelines and APIs.
  • Lead performance and reliability testing for large-scale data lakes, warehouses, and streaming systems.
  • Diagnose and optimize bottlenecks in latency, throughput, and system reliability.
  • Integrate and manage tools such as Great Expectations, dbt, JMeter, Locust, Grafana, Prometheus.
  • Lead a team of SDETs in test automation and data platform QA.
  • Define data quality KPIs with business stakeholders and share actionable insights.
  • Partner with Data/Platform Engineers to embed quality checks into CI/CD pipelines and infrastructure deployments.

Data Engineering & Platform Support (Secondary Focus)

  • Contribute to the design, development, and optimization of ETL/ELT pipelines and data platforms.
  • Support scalable data ingestion, transformation, and storage solutions.
  • Ensure data governance, lineage, and compliance across multi-cloud environments.
  • Collaborate with analytics and BI teams to guarantee reliable data availability for reporting, APIs, and ML models.
  • Contribute to infrastructure automation with Terraform, CloudFormation, or equivalent IaC tools.

Required Qualifications

  • Bachelor’s/Master’s in Computer Science, Information Systems, or related field.
  • 12+ years in software engineering, with 5+ years in Data Engineering/Data Quality and 2+ years in a lead role.
  • Strong programming skills in Java, Python, and SQL.
  • Expertise with automation/testing tools (e.g., Selenium, REST Assured, Postman, Cypress).
  • Experience with RDBMS, NoSQL, and document-oriented databases (PostgreSQL, MongoDB, Elasticsearch).
  • Hands-on with big data & distributed systems (Spark, Kafka, Hadoop).
  • Proven track record in performance engineering and tuning data systems.
  • Experience with at least one major cloud (AWS, Azure, GCP); multi-cloud familiarity preferred.
  • Strong communication and stakeholder engagement skills.

Preferred Qualifications

  • Cloud certifications (AWS, Azure, GCP – Data/DevOps focus).
  • Experience with:
    • Data governance/catalog tools (Collibra, Apache Atlas, Alation).
    • Lakehouse technologies (Delta Lake, Apache Iceberg, Hudi).
    • DataOps/MLOps platforms (MLflow, Kubeflow, TensorFlow).
  • Prior exposure to regulated industries or domain-specific environments (e.g., Hospitality).

Skills

Data Quality Assurance,Data Architecture,Etl Design

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