Lead Data Engineer
Role OverviewThe Lead Data Engineer will serve as a technical leader responsible for defining data architecture, leading the development of scalable and secure data platforms, and driving enterprise-wide data engineering best practices. This role combines hands-on engineering with technical leadership, focusing on building metadata-driven, automated ELT pipelines using Snowflake, Qlik Replicate, dbt Cloud, and AWS services.The position plays a key role in data governance, quality, performance optimization, and release management while partnering closely with business stakeholders to translate data requirements into robust architecture solutions.Key ResponsibilitiesDesign and lead scalable data architecture aligned with business strategyBuild and optimize real-time and batch data pipelines for large-scale data environmentsLead the development of ELT pipelines using Qlik Replicate, Snowflake, dbt Cloud, and CI/CD toolsDrive data governance, security, compliance, and data quality initiativesAnalyze and resolve complex performance and data reliability issuesReview, approve, and manage code deployments across environments including production and DREnforce testing, automation, monitoring, and observability best practicesMentor junior engineers and provide technical guidance to teamsCollaborate with business and leadership teams to deliver data-driven solutionsTechnical & Business SkillsDeep expertise in Snowflake, including medallion architecture, Snowpipe, RBAC, and data maskingStrong hands-on experience with Qlik Replicate, dbt Cloud, and GitLab CI/CDAdvanced proficiency in Python, PySpark, and SQLExperience building pipelines across SQL Server, Oracle, Mainframe DB2, files, and SnowflakeStrong AWS experience: S3, Lambda, Glue, SQS, SNS, RDSExperience with structured and semi-structured data formats (CSV, JSON, XML, Excel, VSAM)Orchestration using dbt Cloud and Astronomer AirflowExperience implementing logging, monitoring, alerting, observability (e.g., Dynatrace)Strong experience with schema drift detection and schema evolutionProven expertise in data security, governance, tokenization, and Snowflake masking policiesFinancial/banking domain experience is a plusOne or more relevant technical certifications required