Enterprise Minds, Inc | Lead Data Engineer

4 days ago

Delhi, India Enterprise Minds, Inc Full time
Job Opening: Data Engineer (7-10 Years Experience)Are you a passionate Data Engineer looking to work in a dynamic and challenging environment?

Job Title:

Data Engineer Lead – Expertise in either* of (Azure, AWS, or Google Cloud)Job Location:

USAExperience:

7-10 years of experienceQualifications: Bachelor's

in engineering (preferably computer science)Job Summary:

We are seeking a highly skilled and experienced Data Engineer Lead to oversee the design, development, and implementation of data solutions across Azure, AWS, and Google Cloud platforms. The ideal candidate will lead a team of data engineers, ensuring the creation of scalable, high-performance data pipelines and analytics solutions to meet business needs.

Key Responsibilities:Leadership & Strategy:Lead a team of data engineers to deliver high-quality data solutions across multiple cloud environments.Define best practices and standards for multi-cloud* data engineering.Collaborate with cross-functional teams, including data scientists, analysts, and product managers, to define comprehensive data strategies.Solution Design & Development:Architect and implement data pipelines using Azure Data Factory, AWS Glue, and Google Dataflow.Design and manage data lake architectures on Azure Data Lake Storage (ADLS), Amazon S3, and Google Cloud Storage.Implement data modeling, data integration, and ETL/ELT pipelines using tools like Azure Synapse, Redshift, and Big Query.Operational Excellence:Optimize workflows to ensure performance, scalability, and cost-efficiency across cloud platforms.Implement CI/CD pipelines for data engineering workflows using Azure DevOps, AWS Code Pipeline, and Google Cloud Build.Monitor and troubleshoot pipelines to address performance issues and ensure resilience.Governance & Security:Ensure compliance with data governance, security policies, and regulations across cloud providers.Use tools like Azure Purview, AWS Glue Data Catalog, and Google Data Catalog for metadata management.Implement best practices for securing data using role-based access control (RBAC), encryption, and managed identities.

CommunicationStakeholder Collaboration : Translate business needs into technical solutions and present updates clearly to non-technical audiences.Team Leadership : Mentor team members, foster collaboration, and provide constructive feedback.Cross-Functional Coordination : Work with product managers, data scientists, and engineers to align data strategies.Documentation : Maintain clear documentation for workflows and project decisions.Conflict Resolution : Resolve team and stakeholder conflicts effectively with strong interpersonal skills.Communication Tools : Use collaboration platforms (e.g., Slack, Jira) to streamline communication.Thought Leadership : Advocate for data engineering initiatives and share insights on industry trends.Adaptability : Tailor communication style to suit technical and non-technical audiences.

Required Skills and Qualifications:Multi-Cloud Expertise (Optional – At least one cloud with proven skill):Proficiency in Azure (Data Factory, Databricks, Synapse Analytics), AWS (Glue, Redshift, S3), and Google Cloud (Dataflow, Big Query, Cloud Storage).Knowledge of streaming services like Azure Event Hubs, AWS Kinesis, and Google Pub/Sub.Programming and Scripting Languages:Strong programming skills in Python, SQL, and optionally Scala for big data processing.Big Data Frameworks and Tools:Expertise in Apache Spark, Scala, Java and other multi-cloud implementations.Skilled in distributed computing frameworks for large-scale data processing.Data Modeling and ETL/ELT Design:Expertise in designing efficient data models for data lakes and warehouses.Hands-on experience creating scalable ETL/ELT pipelines.CI/CD and DevOps:Hands-on experience with multi-cloud* CI/CD tools (Azure DevOps, AWS CodePipeline, Google Cloud Build).Knowledge of Infrastructure as Code (IaC) tools like Terraform, Biceps.Data Governance and Security:Experience with Azure Purview, AWS Glue Data Catalog, and Google Data Catalog.Knowledge of encryption and key management solutions like Azure Key Vault, AWS KMS, and Google Cloud KMS.Additional Knowledge:Familiarity with visualization tools like Power BI, Tableau, or Looker.Understanding of real-time data streaming with Kafka or equivalent.

Certifications (Preferred):AWS Certified Data Analytics – SpecialtyMicrosoft Certified: Azure Data Engineer AssociateGoogle Professional Data EngineerMS Fabric DP-600

Location:

RemoteIf you meet the above qualifications and are ready to take on a challenging role, apply now to be part of our team

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