Data Engineer

About HCLTech

HCLTech is a global technology company, spread across 60 countries, delivering industry-leading capabilities centered around digital, engineering, cloud and AI, powered by a broad portfolio of technology services and products. We work with clients across all major verticals, providing industry solutions for Financial Services, Manufacturing, Life Sciences and Healthcare, Technology and Services, Telecom and Media, Retail and CPG, and Public Services. We are powered by our people a global, diverse, multi-generational talent - representing 161 nationalities whose unique spark, perspective and boundless passion drive our culture of proactive value creation and problem-solving.

Our purpose is to bring together the best of technology and our people to supercharge progress for everyone, everywhere our clients, partners, their stakeholders, communities, and the planet. As a company, we are deeply focused on accelerating our ESG agenda. We are also creating technology-enabled sustainable solutions with and for our clients and partners. We embed ESG imperatives into every aspect of our business and ensure that the progress we supercharge is responsible, inclusive and beneficial to all our stakeholders in the long term. We have committed to achieving net zero by 2040.

To learn more about how we can supercharge progress for you, visit www.hcltech.com

RESPONSIBILITIES:

• Excellent in advance SQL, ETL. Must understand relation and ER diagrams/normal forms. How to design, create, extend/iterate, manipulate, seed with realistic data/data exploration, create and optimize queries, operate at low scale and high scale.
• Experience in creation of data pipelines using Python. Python for data manipulation & transformation (python dictionaries, data frames, data stream, joins of all kinds, outside of SQL IDEs)
• Experience with Data Warehousing Architecture
• Research skills – go figure it out and come back with working model. Pros/cons analysis skills
• Good to have - End to end understanding of data center operations & applying optimizations/automations using data science Education – preferred MS/PHD candidates
• Partner with leadership, software engineers, product managers, program managers and data scientists to understand data needs.
• Act as a subject matter expert in a specific domain or class of data engineering challenges, leading by example and mentoring others.
• Influence short- and long-term strategy with cross-functional teams to drive impact.
• Design, build and launch extremely efficient and reliable data pipelines to move data across a number of platforms including Data Warehouse, online caches and real-time systems.
• Build data expertise and own data quality for allocated areas of ownership Architect, Build and Launch new data models that provide intuitive analytics Work with teams to establish data sources that serve teams' business needs.
• Identifying and advocating for process improvements and industry best practices.
• Work with a variety of inhouse products, applications and warehouses, transforming raw data into finished products to help drive, investigate, monitor, report and quantify the state of risk and compliance.
• Build strategic relationships with global and cross-functional teams to understand and anticipate risks to the company and deliver analytics for monitoring compliance and responding to regulations.
• Educate your partners: Use your data and analytics experience to ‘see what’s missing’, identifying and addressing gaps in their existing logging and processes.

MINIMUM QUALIFICATIONS

• Bachelor's degree in computer science, Computer Engineering, relevant technical field, or equivalent practical experience.
• 2+ years of Python development experience.
• 2+ years of SQL experience.
• 2+ years’ experience in engineering data pipelines using big data technologies (Hive, Presto, Spark, Flink etc.) on large scale datasets.
• 2+ years’ experience with Schema Design and Data Modeling.
• Experience querying massive datasets using Spark, Presto, Hive, Impala, etc.
• 2+ years of experience with workflow management engines (i.e. Airflow, Luigi, Prefect, Dagster, Digdag, Google Cloud Composer, AWS Step Functions, Azure Data Factory, UC4, Control-M).
• Experience working with cloud or on-prem Big Data/MPP analytics platform (i.e. Snowflake, AWS Redshift, Google BigQuery, Azure Data Warehouse, Netezza, Teradata, or similar).