Data Engineer - Python AND Kafka AND (Hadoop OR HDFS OR Hive) AND Snowflake AND apache AND (iceberg

NTT America, Inc.; Bengaluru; On-site; INR 1,500,000 - 2,300,000; Full time

Job summary

NTT DATA seeks a Data Engineer to join the Bangalore team, driving end-to-end datastore migration from on-prem DataLake to AWS LakeHouse. You will translate legacy SQL and Spark consumption to Snowflake and Iceberg, ensuring data quality and alignment with business needs.

You will collaborate with data owners, optimize data patterns, and validate migrated assets while learning new workflows. This role is based in Bengaluru, IN, with a strong focus on collaboration across global teams.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Applied Mathematics, Engineering, or related field.
• 3-5 years hands-on coding in a team environment; strong troubleshooting in SQL and scripting.
• Proficiency in Python or Java.
• SDLC and CI/CD with Kubernetes deployment experience.
• Experience with data modeling and schema evolution concepts.

Responsibilities

• Migrate datastore end-to-end from on-prem DataLake to AWS LakeHouse.
• Refactor and migrate extraction logic and job scheduling to Lakehouse environment.
• Translate legacy SQL/Spark patterns for Snowflake and Iceberg compatibility.
• Ensure data integrity during materialization and migration.
• Validate migrated data using reconciliation frameworks and coordinate with data owners.

Skills

Python

Kafka

Hadoop

Hive

Snowflake

Iceberg

SQL

Education

Bachelor’s or Master’s in CS/Engineering/Math

Tools

Apache Spark

Snowflake

Iceberg

Hadoop

HDFS

Hive

Job description

NTT DATA strives to hire exceptional, innovative and passionate individuals who want to grow with us. If you want to be part of an inclusive, adaptable, and forward-thinking organization.

We are currently seeking a Data Engineer - Python AND Kafka AND (Hadoop OR HDFS OR Hive) AND Snowflake AND apache AND iceberg to join our team in Bangalore, Karnātaka (IN-KA), India (IN).

Responsibilities

Engineer will be part of the datastore-migration Factory team that will be responsible to perform for the end-to-end datastore migration from on-prem DataLake to AWS hosted LakeHouse. This is a high visibility and crucial project for Goldman Sachs.

Responsibilities of the Engineer includes

Pipeline Migration

Logic & Scheduling: Refactoring and migrating extraction logic and job scheduling from legacy frameworks to the new Lakehouse environment.

Data Transfer: Executing the physical migration of underlying datasets while ensuring data integrity.

Stakeholder Engagement: Acting as a technical liaison to internal clients, facilitating "handoff and sign-off" conversations with data owners to ensure migrated assets meet business requirements.

Consumption Pattern Migration

Code Conversion: Translating and optimizing legacy SQL and Spark-based consumption patterns (raw and modeled) for compatibility with Snowflake and Iceberg.

Usage analysis: Understand usage patterns to deliver the required data products.

Stakeholder Engagement: Acting as a technical liaison to internal clients, facilitating "handoff and sign-off" conversations with data owners to ensure migrated assets meet business requirements.

Data Reconciliation & Quality

A rigorous approach to data validation is required. Candidates must work with reconciliation frameworks to build confidence that migrated data is functionally equivalent to that already used within production flows.

Engineer will also need to work with our other internal data management platform, and must have an aptitude for learning new workflows and language constructs as necessary.

Technical Skills

Basic Qualifications

Education: Bachelor’s or Master’s degree in Computer Science, Applied Mathematics, Engineering, or a related quantitative field.

Experience: Minimum of 3-5 years of professional "hands-on-keyboard" coding experience in a collaborative, team-based environment. Ability to trouble shoot (SQL) and basic scripting experience.

Languages: Professional proficiency in Python or Java.

Methodology: Deep familiarity with the full Software Development Life Cycle (SDLC) and CI/CD best practices & K8s deployment experience.

Core Data Engineering Competencies: Candidates must demonstrate a sophisticated understanding of the following modeling concepts to ensure data correctness during reconciliation:

Temporal Data Modeling: Managing state changes over time (e.g., SCD Type 2).

Schema Management: Expertise in Schema Evolution (Ref: Iceberg Apache) and enforcement strategies.

Performance Optimization: Advanced knowledge of data partitioning and clustering.

Architectural Theory: Balancing Normalization vs. Denormalization and the strategic use of Natural vs. Surrogate Keys.

Technical Stack Requirements

While candidates are not expected to be experts in every tool, the collective team must cover the following technologies:

Extraction & Logic

• Kafka, ANSI SQL, FTP, Apache Spark

Data Formats

• JSON, Avro, Parquet

Platforms

• Hadoop (HDFS/Hive), Snowflake, Apache Iceberg, Sybase IQ

Core Competencies

• Demonstrates strong integrity and consistently models good conduct and ethical decision-making.
• Acts as a trusted team player who collaborates effectively across multiple teams and functions.
• Communicates with clarity and confidence - concise written updates, structured verbal briefings, and proactive stakeholder management.
• Works effectively with global teams across time zones and cultures; builds alignment and resolves issues constructively.
• Delivery-focused with a strong sense of ownership; drives work to closure and meets commitments.
• Brings high energy and urgency to achieve targets while maintaining quality and professionalism.
• Shows intellectual curiosity; asks thoughtful questions, surfaces risks early, and seeks feedback to continuously improve.

About NTT DATA

NTT DATA is a $30 billion business and technology services leader, serving 75% of the Fortune Global 100. We are committed to accelerating client success and positively impacting society through responsible innovation. We are one of the world's leading AI and digital infrastructure providers, with unmatched capabilities in enterprise-scale AI, cloud, security, connectivity, data centers and application services. our consulting and Industry solutions help organizations and society move confidently and sustainably into the digital future. As a Global Top Employer, we have experts in more than 50 countries. We also offer clients access to a robust ecosystem of innovation centers as well as established and start-up partners. NTT DATA is a part of NTT Group, which invests over $3 billion each year in R&D.

Whenever possible, we hire locally to NTT DATA offices or client sites. This ensures we can provide timely and effective support tailored to each client’s needs. While many positions offer remote or hybrid work options, these arrangements are subject to change based on client requirements. For employees near an NTT DATA office or client site, in-office attendance may be required for meetings or events, depending on business needs. At NTT DATA, we are committed to staying flexible and meeting the evolving needs of both our clients and employees.

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