Position Overview:

We are seeking a highly experienced Data Analyst with deep expertise in ETL processes, Big Data technologies, and modern data platforms. The ideal candidate will have extensive hands-on experience with tools such as Talend, MarkLogic, Master Data Management (MDM), Databricks, Snowflake, and Azure Data Factory. This role involves driving data integration, transformation, and analytics initiatives in a fast-paced, remote environment, supporting enterprise-scale data projects.

Key Responsibilities:

Design, develop, and maintain ETL pipelines using Talend, Azure Data Factory, or similar tools to support large-scale data ingestion and transformation.

Work extensively with Big Data platforms including Databricks and Snowflake for scalable data processing and storage.

Implement and manage Master Data Management (MDM) solutions to ensure data consistency and accuracy across systems.

Develop and optimize queries and workflows within MarkLogic and other NoSQL databases.

Collaborate with cross-functional teams to understand business requirements and translate them into technical data solutions.

Perform data profiling, data cleansing, and validation to ensure high data quality.

Create and maintain documentation including data mappings, process flows, and technical specifications.

Monitor ETL jobs and data pipelines to ensure performance, reliability, and error handling.

Participate in architecture design sessions to enhance data infrastructure and analytics capabilities.

Support data governance and compliance initiatives related to data security and privacy.

Required Skills and Qualifications:

7+ years of experience as a Data Analyst or similar role with strong focus on ETL and Big Data technologies.

Proficient in ETL tools such as Talend and Azure Data Factory.

Hands-on experience with Big Data platforms including Databricks and Snowflake.

Solid understanding and experience working with Master Data Management (MDM) concepts and tools.

Experience working with MarkLogic or other NoSQL databases.

Strong SQL skills and experience with data warehousing concepts.

Familiarity with scripting languages like Python or Shell for automation tasks.

Knowledge of data governance, data security, and compliance standards.

Ability to work independently in a remote environment with minimal supervision.Excellent problem-solving, analytical, and communication skills.

Preferred Qualifications:

Experience in cloud environments such as Azure, AWS, or GCP.

Knowledge of containerization (Docker, Kubernetes) and CI/CD pipelines.

Experience with data visualization tools (Tableau, Power BI).

Certification in Talend, Snowflake, or cloud data platforms.