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Data Engineer/Senior Data Engineer

2 months ago

Gurugram, India Cognitio Analytics Inc Full time

Experience:


1 to 8 years - DE/ Sr. DE/ AM /Manager


Must Have:

  • SQL
  • Python/ Pyspark
  • Azure Databricks, ADLS Gen 2 Blob Storage, Key Vaults, BitBucket, Version control, Azure DevOps
  • ETL, Building Data Pipelines, Data Warehousing, Data Modelling and Governance, Data Security
  • Agile Practices, SDLC
  • Data Exploration, Data Quality metrics, Historical data Management, Good problem-solving skill
  • Excellent Comm Skills
  • Exp in Data Engineering domain: 2+ Years.
  • Multi years’ experience with Azure-Databricks ecosystem and Py spark.
  • Ability to write clean, concise and organized Py spark code.
  • Ability to break down the project into executable steps, prepare a DFD and execute the same
  • Propose innovative DE solutions to achieve business objectives.
  • Quick on his feet, good at tech and logically complex communication
  • Good Knowledge of ADF, Docker /containerization.


Good to have:

  • Event Hubs
  • Any kind of health care background eg, - Pharma
  • Azure Data Factory, Cosmos DB, Power BI, Azure Synapse
  • Competitive coding and knows most Py spark syntax by heart.

Job Description:

We are seeking a highly skilled Azure Cloud Data Engineer to join our dynamic team. As an Azure Cloud Data Engineer, you will be responsible for designing, implementing, and managing cloud-based data solutions using Microsoft Azure. The ideal candidate should have a strong background in data engineering, with hands-on experience in Azure services and tools.


Essential Job Duties & Responsibilities:

  • Set up workflows and orchestration processes to streamline data pipelines and ensure efficient data movement within the Azure ecosystem.
  • Create and configure compute resources within Databricks, including All-Purpose and SQL Compute and Job Clusters to support data processing and analysis.
  • Set up and manage Azure Data Lake (ADLS) Gen 2 storage accounts and establish a seamless integration with Databricks Workspace for data ingestion and processing.
  • Create and manage Service Principals, key vaults to securely authenticate and authorize access to Azure resources.
  • Utilize ETL (Extract, Transform, Load) techniques to design and implement data warehousing solutions and ensure compliance with data governance policies.
  • Develop highly automated ETL scripts for data processing.
  • Scale infrastructure resources based on workload requirements, optimizing performance and cost-efficiency.
  • Profile new data sources in a different format including CSVs, JSONs etc.
  • Apply problem-solving skills to address complex business and technical challenges, such as data quality issues, performance bottlenecks, and system failures.
  • Demonstrate excellent soft skills and the ability to effectively communicate and collaborate with clients, stakeholders, and cross-functional teams.
  • Implement Continuous Integration/Continuous Deployment (CI/CD) practices to automate the deployment and testing of data pipelines and infrastructure changes.
  • Delivering tangible value very rapidly, collaborating with diverse teams of varying backgrounds and disciplines.
  • Codifying best practices for future reuse in the form of accessible, reusable patterns, templates, and code bases.
  • Manage timely appropriate communication and relationship with clients, partners and other stakeholders.
  • Create and manage periodic reporting of project execution status and other trackers in standard accepted formats.

Required Competencies:

  • Strong proficiency in SQL for data manipulation, querying, and optimization.
  • Proficiency in Python and PySpark for data engineering and data processing tasks.
  • Solid understanding of the Microsoft Azure tooling for large-scale data engineering efforts and deployments is highly preferred.
  • Hands-on experience with Azure Databricks, including data ingestion, transformation, and analysis.
  • Ability to set up and manage Azure Data Lake Storage (ADLS) Gen 2 accounts, and familiarity with data lake architecture and best practices.
  • Knowledge of Azure Key Vaults for securely storing and managing cryptographic keys, secrets, and certificates.
  • An ‘engineering’ mindset, willing to make rapid, pragmatic decisions to improve performance, accelerate progress or magnify impact.
  • Comfort with working with distributed teams on code-based deliverables, using version control systems and code reviews.
  • Use of agile and DevOps practices for project and software management including continuous integration and continuous delivery.
  • Ability to conduct data analysis, investigation, and lineage studies to document and enhance data quality and access.
  • Proven track record of scaling infrastructure to meet performance and scalability requirements.
  • Strong analytical and problem-solving skills, with the ability to troubleshoot complex technical issues.
  • Direct experience having built and deployed robust, complex production systems.
  • Proficiency in Event Hubs and Azure Data Factory, particularly in the context of data streaming and transfer.


Qualifications:

  • Bachelor’s degree in computer science, Engineering, or a quantitative discipline.
  • 2+ years of professional experience as an Azure Cloud Data Engineer or a similar role.
  • Excellent communication skills, both verbal and written.
  • Strong attention to detail and the ability to work in a fast-paced environment.