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

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