Data Engineer

A Data Engineer is a data professional who uses their expertise in data engineering and programming to build systems that collect, manage and convert raw data into usable information for business analysts.

Responsibilities

As a Data Engineer

ü Analyze and organize raw data

ü Build data systems and pipelines

ü Evaluate business needs and objectives

ü Interpret trends and patterns

ü Conduct complex data analysis and report on results

ü Prepare data for prescriptive and predictive modeling

ü Build algorithms and prototypes

ü Combine raw information from different sources

ü Explore ways to enhance data quality and reliability

ü Identify opportunities for data acquisition

ü Collaborate with data scientists, business analysts, BI developers, and architects on several projects

ü Familiarize and understand of key business processes, tools and metrics

ü Ability to facilitate meetings and gather requirements from stakeholders

ü Effectively and proactively communicates with stakeholders, team-members and other support teams to promote synergy

ü Perform timely ad-hoc supports requests in support of business needs, escalations and/or process improvement initiatives

ü Manage end-to-end data-related requests completion in a timely manner

ü Create detailed process-flow and or documentations for all requests/projects handled

ü Identify and drive internal needs for improvements with the way we deliver our projects and the way we work

Qualifications

· Bachelor's degree in related field.

· At least 5 to 10 years' previous experience as a data engineer or in a similar role

· Technical expertise with data models, data mining, and segmentation techniques

· Knowledge of programming languages (e.g. Java and Python)

· Advanced Hands-on experience with SQL database design and Databricks

· Great numerical and analytical skills

· Degree in Computer Science, IT, or similar field; a Master's is a plus

· Data engineering certification (e.g IBM Certified Data Engineer) is a plus

· Experience/Knowledge in using Salesforce, Sap, Oracle, Genesys is a plus

· Ability to perform analysis, formulated conclusions and recommend actions.

· Excellent verbal and written communication skills. Fluency in English required.

· Ability to communicate and work with cross-functional teams and cross-country stakeholders is a must.

· Strong organizational skills

· Experience with project management is a plus

· Highly motivated and eager to learn new applications and/or tools

· Displays a positive and team first attitude

· Continuously seeks ways to enhance contribution to those they support

· Supports hybrid work model. Work at Home and Work at On-Site.

· Must be able to juggle many multiple projects simultaneously.

Technical Skills

• Apache Spark Proficiency
• Deep understanding of Spark core concepts: RDDs, DataFrames, Spark SQL, Spark Streaming, and MLlib.
• Experience tuning Spark jobs for performance and cost efficiency
• Delta Lake Expertise
• Familiarity with Delta Lake operations like upserts, Z-ordering, and VACUUM.
• Understanding of ACID transactions and schema enforcement in data lakes
• Programming Languages
• Strong skills in Python or Scala (Java is also useful).
• Ability to write efficient, scalable ETL pipelines
• SQL and Database Management
• Advanced SQL skills for querying structured data.
• Experience with relational (e.g., MySQL) and NoSQL databases (e.g., MongoDB, Cassandra)
• Cloud Platform Knowledge
• Hands-on experience with Azure.
• Understanding of cloud resource management and cost optimization
• Data Warehousing & Modeling
• Familiarity with data warehousing concepts and tools like Snowflake.
• Experience in designing scalable data models
• Soft Skills & Other Capabilities

· Problem-solving and analytical thinking

· Collaboration and communication skills, especially for cross-functional teams

· Consulting mindset for client-facing roles or internal stakeholder engagement

1. Certifications (e.g., Databricks Certified Data Engineer Associate or Professional) are a strong plus

Job Type: Full-time

Work Location: In person