Data Engineer

We are HCLTech, one of the fastest-growing large tech companies in the world and home to 219,000+ people across 54 countries, supercharging progress through industry-leading capabilities centered around Digital, Engineering and Cloud.

The driving force behind that work, our people, are diverse, creative, and passionate, raising the bar for excellence on a regular basis. We, in turn, work hard to bring out the best in them as we strive to help them find their spark and become the best version of themselves that they can be.

We are on the lookout for a highly talented and self-motivated Data Engineer to join us on our journey in advancing the technological world through innovation and creativity.

Job Title: Data Engineer (PySpark)

About the Role: -

We are seeking a highly skilled Data Engineer with deep expertise in PySpark and the Cloudera Data Platform (CDP) to join our data engineering team. As a Data Engineer, you will be responsible for designing, developing, and maintaining scalable data pipelines that ensure high data quality and availability across the organization. This role requires a strong background in big data ecosystems, cloud-native tools, and advanced data processing techniques.

The ideal candidate has hands-on experience with data ingestion, transformation, and optimization on the Cloudera Data Platform, along with a proven track record of implementing data engineering best practices. You will work closely with other data engineers to build solutions that drive impactful business insights.

Responsibilities: -

Data Pipeline Development: Design, develop, and maintain highly scalable and optimized ETL pipelines using PySpark on the Cloudera Data Platform, ensuring data integrity and accuracy.

Data Ingestion: Implement and manage data ingestion processes from a variety of sources (e.g., relational databases, APIs, file systems) to the data lake or data warehouse on CDP.

Data Transformation and Processing: Use PySpark to process, cleanse, and transform large datasets into meaningful formats that support analytical needs and business requirements.

Performance Optimization: Conduct performance tuning of PySpark code and Cloudera components, optimizing resource utilization and reducing runtime of ETL processes.

Data Quality and Validation: Implement data quality checks, monitoring, and validation routines to ensure data accuracy and reliability throughout the pipeline.

Automation and Orchestration: Automate data workflows using tools like Apache Oozie, Airflow, or similar orchestration tools within the Cloudera ecosystem.

Monitoring and Maintenance: Monitor pipeline performance, troubleshoot issues, and perform routine maintenance on the Cloudera Data Platform and associated data processes.

Collaboration: Work closely with other data engineers, analysts, product managers, and other stakeholders to understand data requirements and support various data-driven initiatives.

Documentation: Maintain thorough documentation of data engineering processes, code, and pipeline configurations.

Qualifications: -

Education and Experience: -

1. Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.
2. 3+ years of experience as a Data Engineer, with a strong focus on PySpark and the Cloudera Data Platform.

Technical Skills: -

• PySpark: Advanced proficiency in PySpark, including working with RDDs, DataFrames, and optimization techniques.
• Cloudera Data Platform: Strong experience with Cloudera Data Platform (CDP) components, including Cloudera Manager, Hive, Impala, HDFS, and HBase.
• Data Warehousing: Knowledge of data warehousing concepts, ETL best practices, and experience with SQL-based tools (e.g., Hive, Impala).
• Big Data Technologies: Familiarity with Hadoop, Kafka, and other distributed computing tools.
• Orchestration and Scheduling: Experience with Apache Oozie, Airflow, or similar orchestration frameworks.
• Scripting and Automation: Strong scripting skills in Linux.

Soft Skills: -

1. Strong analytical and problem-solving skills.
2. Excellent verbal and written communication abilities.
3. Ability to work independently and collaboratively in a team environment.
4. Attention to detail and commitment to data quality.

Why Us: -

We are one of the fastest-growing large tech companies in the world, with offices in 50+ countries across the globe and 219,000 employees,

• Our company is extremely diverse with 165 nationalities represented.
• We offer the opportunity to work with colleagues across the globe.
• We offer a virtual-first work environment, promoting a good work-life integration and real flexibility.
• We offer comprehensive benefits for all employees.
• We are a certified great place to work and a top employer in 17 countries, offering a positive work environment that values employee recognition and respect.

Equality & Opportunity for All: -

Representing 165 nationalities across the globe, we pride ourselves on being an equal opportunity employer, committed to providing equal employment opportunities to all applicants and employees regardless of race, religion, sex, color, age, national origin, pregnancy, sexual orientation, physical disability or genetic information, military or veteran status, or any other protected classification, in accordance with federal, state, and/or local law.