Development and optimization of scalable data pipelines for efficient extraction, transformation, and loading (ETL) of data from diverse sources, leveraging technologies like Spark, Dask, and other modern ETL frameworks.
Develop and implement data quality controls, including monitoring and remediation processes
Provide technical guidance and mentorship to junior ETL developers
Collaborate with the infrastructure team to ensure the availability, reliability, and scalability of ETL solutions
Participate in code reviews and contribute to the development of coding standards and best practices
Stay up-to-date with emerging trends and technologies in ETL development and data management
Architect and implement advanced data models for both NoSQL (e.g., HBase) and relational databases, ensuring high performance, scalability, and cost efficiency in data storage and retrieval processes.
Establish robust systems to ensure data quality, implementing monitoring tools and validation frameworks to guarantee accuracy and availability of production data for key business stakeholders.
Design, build, and maintain high-performance APIs to provide seamless access to curated data sets for both internal teams and external clients.
Oversee the assembly of large, complex data sets that meet functional, non-functional, and business requirements, enabling data-driven decision-making across the organization.
Conduct root cause analysis on internal and external data and processes to resolve business inquiries, support client requests, and proactively identify areas for system and process improvement.
Collaborate closely with cross-functional teams, providing leadership and technical guidance to ensure alignment on data architecture and delivery goals.
Technical Requirements :
2+ years of experience in developing, testing, and maintaining applications using Python, Bash, and SQL, with a focus on delivering scalable solutions.
Strong expertise in writing clean, efficient, and maintainable code, with a deep understanding of design patterns and best practices.
In-depth knowledge of SQL and NoSQL databases, including database design and optimization techniques.
Extensive experience with parallel processing and distributed computing frameworks like Hadoop, Spark, or Dask.
Proven track record in custom ETL design, implementation, and operational maintenance in complex environments.
Familiarity with ETL orchestration frameworks such as Luigi, Apache Airflow, or Apache NiFi is an advantage.
Proficiency in backend frameworks like Django or Flask, with demonstrated experience in building and maintaining web services and APIs.
Strong experience with cloud platforms (AWS, GCP, Microsoft Azure), including cloud-based data storage and processing solutions.
Exposure to data analytics, data science, or machine learning workflows is a plus.
(ref : hirist.tech)
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Etl Developer • Vijayawada
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