Cognitio Analytics Inc | Data Engineer/Senior Data Engineer | india
5 days ago
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.
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