Data & Analytics Solutions Architect (Open-source Data Applications / Tools / Platforms

Tata Consultancy Services; New York (NY); On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Discretionary Annual Incentive

Comprehensive Medical Coverage

Family Support: Leaves

Insurance Options: 401K & More

Certification & Training Reimbursement

Job summary

Tata Consultancy Services Limited in New York City area seeks a senior Architect with 14+ years of enterprise data experience. You will design end-to-end, open-source data platforms for batch, streaming, analytics, and AI workloads, lead modernization efforts, and ensure secure, scalable, and observable environments.

Role requires strong leadership, stakeholder management, and hands-on expertise with Spark, Kafka, and data lakehouse technologies. Travel may be required for client engagements.

Qualifications

• 14+ years of enterprise data architecture and data engineering experience.
• Experience across data to insights end-to-end value chain.
• Hands-on with Spark, PySpark, Kafka, Flink, Airflow, NiFi, Trino.
• Designing open-source data platform architectures and modern Lakehouse solutions.
• Experience with batch, streaming, and real-time processing.
• Knowledge of data governance, security, RBAC, and privacy controls.
• Proficiency with Iceberg, Hudi, Delta Lake architectures.
• Experience with Kubernetes and CI/CD in DataOps.

Responsibilities

• Engage with stakeholders to understand data strategy, platform requirements, architecture goals, and transformation priorities.
• Define end-to-end architecture for enterprise open-source data platforms supporting batch, streaming, analytics, and AI workloads.
• Lead modernization of data lakes, lakehouse platforms, and distributed processing frameworks.
• Architect scalable, secure, highly available data platforms using open-source technologies.
• Define data ingestion, integration, streaming, storage, and consumption patterns with Spark, Kafka, Flink, NiFi, Trino.
• Establish data governance, metadata, lineage, privacy, and observability standards across the platform.

Skills

Enterprise Data Architecture

Open-Source Data Platforms

Distributed Data Processing

Data Engineering

Apache Spark

PySpark

Kafka

Flink

Airflow

NiFi

Trino

SQL

Python

Scala

Java

Data Lakehouse

DataOps

CI/CD

Observability

Metadata Governance

Kubernetes

RBAC & Security

Cloud Migration

Education

Bachelor's degree in Computer Science / Engineering / Information Systems

Cloud Data Engineering Certification

Kubernetes Certification

Tools

PostgreSQL

Cassandra

MongoDB

OpenSearch

Job description

Job Description

Location: NJ/NYC/ Pittsburg

Must Have Technical/Functional Skills

• 14+ years of experience in Enterprise Data Architecture, Open-Source Data Platforms, Distributed Data Processing, and Data Engineering.
• Proven experience in Enterprise Solution architecture using Open source technology stack across the Data to Insights end to end value chain.
• Strong hands-on expertise in Apache Spark, PySpark, Kafka, Flink, Airflow, NiFi, Trino, SQL, Python, Scala, and Java.
• Proven experience in designing and implementing open-source data platform architectures, including component selection, integration, scalability, interoperability, and platform modernization.
• Deep understanding of batch, streaming, and real-time data processing architectures, including performance tuning, workload optimization, and failure recovery.
• Experience building modern Data Lakehouse architectures using Apache Iceberg, Hudi, Delta Lake, object storage, and open table formats.
• Strong knowledge of event-driven architectures, CDC, APIs, schema management, and enterprise integration patterns.
• Expertise in DataOps practices, including Airflow orchestration, CI/CD, automated testing, observability, metadata management, lineage, and platform operations.
• Experience with PostgreSQL, Cassandra, MongoDB, OpenSearch, and enterprise analytics platforms, including data modeling, indexing, workload management, and availability design.
• Strong understanding of security, governance, and compliance, including RBAC, identity management, encryption, privacy controls, auditability, metadata governance, and vulnerability management.
• Proven ability to lead architecture definition, HLD/LLD creation, NFR assessment, migration planning, technical governance, and production readiness activities.
• Experience supporting large-scale data platform modernization, cloud migration, solutioning, RFP responses, effort estimation, and client-facing architecture discussions.
• Good understanding of BFSI regulatory, security, resilience, privacy, and operational requirements.
• Bachelor's degree in computer science, Engineering, Information Systems, Data Management, or a related discipline.
• Preferred certifications in Cloud Data Engineering, Kubernetes, Enterprise Architecture, Data Management, Security, DevOps, or Open-Source Data Platforms.
• Experience assessing business use cases and selecting the appropriate approach across BI/KPI reporting, rules, statistical methods, forecasting, machine learning, and GenAI, with clear baselines, acceptance criteria, and measurable business KPIs.
• Understanding of AI/ML platform architecture supporting feature engineering, model training, batch and real-time inference, and integration of ML and GenAI workloads with enterprise open-source data platforms.
• Understanding of MLOps and LLMOps capabilities, including experiment tracking, model registry, feature stores, pipeline orchestration, automated quality gates, and versioning of data, models, and prompts using tools such as MLflow and Kubeflow.
• Exposure to AI observability and monitoring for data drift, model drift, LLM quality, tracing, latency, availability, alerting, and operational runbooks.

Roles & Responsibilities

• Engage with business and technology stakeholders to understand data strat egy, platform requirements, architecture goals, and transformation priorities.
• Design and define end-to-end architecture for enterprise open-source data platforms supporting batch, streaming, analytics, and AI workloads.
• Lead modernization initiatives covering data lakes, lakehouse platforms, distributed processing frameworks, and enterprise data ecosystems.
• Architect scalable, secure, highly available, and resilient data platforms using open-source technologies and industry best practices.
• Design data ingestion, integration, streaming, storage, and consumption patterns using technologies such as Spark, Kafka, Flink, NiFi, and Trino.
• Establish data governance, security, metadata, lineage, privacy, and observability standards across the platform landscape.
• Evaluate and recommend open-source technologies based on business requirements, scalability, supportability, interoperability, and total cost of ownership.
• Define architecture standards, reference architectures, reusable frameworks, CI/CD practices, and DataOps operating models.
• Provide technical leadership across data modeling, data engineering, platform implementation, migration, testing, deployment, and production readiness activities.
• Drive platform performance optimization, capacity planning, reliability engineering, and operational excellence initiatives.
• Conduct architecture reviews, identify risks early, and guide delivery teams on mitigation strategies and best practices.
• Support solutioning, RFP responses, effort estimation, technical presentations, and client workshops for strategic opportunities.
• Collaborate with engineering teams, platform vendors, open-source communities, and client stakeholders to deliver scalable and sustainable solutions.
• Mentor architects and engineers, contribute to technical capability development, and establish reusable accelerators, playbooks, and best practices.
• Support hiring, technical assessments, and knowledge-sharing initiatives across Data Engineering, Open-Source Platforms, and Modern Data Architecture.
• Assess candidate use cases with business, technology, data, and risk stakeholders; recommend BI, rules, analytics, ML, or GenAI based on feasibility, risk, cost, and measurable business outcomes.
• Integrate data, ML, and GenAI reference architectures covering data sources, feature pipelines, models or LLMs, vector stores, serving layers, consuming applications, and enterprise integration points.
• Partner with platform and operations teams to productionize AI ML and LLM workloads on Kubernetes.

Generic Managerial Skills, If any

• Strong leadership and stakeholder management skills with the ability to work effectively across business, architecture, engineering, operations, and executive teams.
• Excellent communication and presentation skills, with the ability to simplify complex technical concepts for both technical and non-technical audiences.
• Strong consulting and problem-solving mindset with the ability to evaluate alternatives, challenge assumptions, and recommend practical solutions.
• Proven ability to lead distributed, cross-functional teams and drive alignment across multiple stakeholders and workstreams.
• High level of ownership, accountability, and attention to detail with a focus on quality delivery and customer success.
• Strong planning, prioritization, and decision-making skills with the ability to manage multiple initiatives in a fast-paced environment.
• Experience mentoring architects and engineers, fostering collaboration, knowledge sharing, and technical excellence.
• Ability to manage risks, dependencies, and escalations proactively while ensuring successful project outcomes.
• Strong client-facing experience supporting discovery workshops, solution reviews, architecture governance, and executive discussions.
• Adaptability and resilience to work across evolving technologies, business priorities, and transformation programs.

TCS Employee Benefits Summary:

• Discretionary Annual Incentive.
• Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
• Family Support: Maternal & Parental Leaves.
• Insurance Options: Auto & Home Insurance, Identity Theft Protection.
• Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
• Time Off: Vacation, Time Off, Sick Leave & Holidays.
• Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.
• Salary Range: $140,000 - $180,000 a year

Location

new york city, NY

Function

TECHNOLOGY

Role

Engineer

ID

435899

Skills

Java | Kafka | Apache Spark

Salary Range

$140,000 - $180,000

Desired Candidate Profile

Qualifications

BACHELOR OF COMPUTER SCIENCE