Data Analytics/Integration Engineer

A Data Analytics Integration Engineer is responsible for designing, developing, and managing the integration of data from various sources into analytics platforms, ensuring high-quality data pipelines, and enabling insightful reporting and analysis. The role bridges the gap between data engineering, integration, and analytics teams, supporting decision-making through reliable data processes. Key Responsibilities : Data Integration : - Design and implement data integration pipelines to collect, transform, and load data from diverse sources into analytics platforms. - Ensure seamless integration of data from structured, semi-structured, and unstructured data sources (e.g., databases, APIs, flat files). ETL/ELT Development : - Develop ETL/ELT processes to cleanse, transform, and aggregate data for reporting and analytics purposes. - Optimize data workflows for performance and scalability. Collaboration and Requirements Gathering : - Work closely with business analysts, data scientists, and other stakeholders to understand data requirements. - Translate business needs into technical specifications for data integration solutions. Data Quality and Governance : - Implement and enforce data quality checks to ensure accuracy, completeness, and consistency of integrated data. - Adhere to data governance standards and compliance regulations, including data privacy and security. Platform and Tool Management : - Maintain and configure data integration platforms and tools (e.g., Talend, Informatica, Apache Nifi, Azure Data Factory, or similar). - Monitor and troubleshoot integration processes to address failures and ensure uptime. Analytics Enablement : - Collaborate with analytics teams to create datasets and models optimized for visualization and decision-making. - Support reporting and dashboarding tools like Power BI, Tableau, or Looker by integrating relevant datasets. Documentation : - Create and maintain comprehensive documentation for data workflows, integrations, and processes. - Document best practices and ensure knowledge sharing within the team. Innovation and Continuous Improvement : - Stay updated with emerging data integration tools and techniques. - Recommend and implement improvements to data integration architectures. Required Skills and Qualifications : Technical Expertise : - Proficiency in ETL/ELT tools like Informatica, Talend, Apache Nifi, or Azure Data Factory. - Strong SQL skills for data extraction, transformation, and optimization. - Experience with data warehouse solutions like Snowflake, Redshift, or BigQuery. - Familiarity with scripting languages (e.g., Python, Java, or Scala) for data transformation tasks. Data Knowledge : - Solid understanding of data modeling, data warehousing, and database architecture. - Familiarity with APIs and methods for integrating external data sources. Analytics and BI Tools : - Experience with visualization and analytics tools like Tableau, Power BI, Looker, or Qlik. - Knowledge of creating datasets for business reporting purposes. Soft Skills : - Strong problem-solving and analytical skills. - Excellent communication and interpersonal abilities to work with cross-functional teams. - Attention to detail and commitment to maintaining high-quality data standards. Preferred Qualifications : - Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field. - 3 years of experience in data integration or related roles. - Knowledge of cloud platforms like AWS, Azure, or GCP for data integration and analytics. - Experience with big data frameworks such as Spark, Hadoop, or Kafka. - Certifications in relevant tools/platforms (e.g., Informatica, Azure Data Engineer). A Data Analytics Integration Engineer ensures that data flows smoothly across systems, supports analytical initiatives, and empowers decision-makers with accurate and timely insights. This role is vital for organizations aiming to leverage their data effectively. (ref:hirist.tech)

Location: bangalore, IN

Posted Date: 11/29/2024