Job Description
Data Engineer (Contract) – India We are seeking a hands-on Data Engineer to build, enhance, and operate data pipelines and data products on AWS. This is a contract position based in India, working closely with onsite and offshore engineering partners to deliver reliable, well-governed datasets for analytics and reporting. The Impact: • Build and enhance ELT/ETL pipelines to ingest, transform, and curate data from multiple sources into clean, trusted datasets. • Develop and maintain data processing jobs using Spark and Python, with a focus on performance and reliability. • Implement and monitor data quality checks, reconcile issues, and partner with analysts to resolve data defects. • Translate requirements into technical tasks and deliver well-documented solutions, including runbooks and operational playbooks. • Support day-to-day operations of data pipelines—monitoring, incident triage, root-cause analysis, and meeting SLA targets. • Develop workflows and scheduling using MWAA (Airflow) and AWS-native services. • Collaborate effectively across time zones with onsite stakeholders and the India engineering team through clear communication and proactive status updates. The Minimum Qualifications: • Bachelor’s degree in computer science, Engineering, Information Systems, or related technical field (or equivalent practical experience). • 7+ years of hands-on data engineering experience building and supporting production data pipelines. • Strong SQL skills (design, tuning, troubleshooting) and experience working with relational and analytical data stores. • 3+ years of coding/scripting experience with Python (Java/Scala a plus). • 3+ years of experience on AWS (e.g., S3, Glue, EMR, Lambda, IAM, CloudWatch, MWAA/Airflow). • 2+ years of experience with infrastructure-as-code and CI/CD practices (Terraform preferred). • 2+ years of experience with Spark; streaming experience with Kafka is a plus. • Experience leveraging AI tools (e.g., GenAI assistants) to improve productivity, with an understanding of secure and responsible usage. The Ideal Qualifications • Self-driven, delivery-focused, and comfortable working in a contract environment with clear milestones and timelines. • Curious and methodical—able to research new data sources, open-source tools, and ingestion patterns to propose practical approaches. • Strong operational mindset: observability, alerting, incident response, and continuous improvement to reduce pipeline failures. • Clear communicator with strong stakeholder management skills; able to surface risks early and provide crisp status updates. • Familiarity with domain areas such as Portfolio Management, Cyber Security, and ServiceNow reporting is a plus.
Responsibilities
Exp – 8 to 9 years
Hyd
Job Description
Data Engineer (Contract) – India We are seeking a hands-on Data Engineer to build, enhance, and operate data pipelines and data products on AWS. This is a contract position based in India, working closely with onsite and offshore engineering partners to deliver reliable, well-governed datasets for analytics and reporting. The Impact: • Build and enhance ELT/ETL pipelines to ingest, transform, and curate data from multiple sources into clean, trusted datasets. • Develop and maintain data processing jobs using Spark and Python, with a focus on performance and reliability. • Implement and monitor data quality checks, reconcile issues, and partner with analysts to resolve data defects. • Translate requirements into technical tasks and deliver well-documented solutions, including runbooks and operational playbooks. • Support day-to-day operations of data pipelines—monitoring, incident triage, root-cause analysis, and meeting SLA targets. • Develop workflows and scheduling using MWAA (Airflow) and AWS-native services. • Collaborate effectively across time zones with onsite stakeholders and the India engineering team through clear communication and proactive status updates. The Minimum Qualifications: • Bachelor’s degree in computer science, Engineering, Information Systems, or related technical field (or equivalent practical experience). • 7+ years of hands-on data engineering experience building and supporting production data pipelines. • Strong SQL skills (design, tuning, troubleshooting) and experience working with relational and analytical data stores. • 3+ years of coding/scripting experience with Python (Java/Scala a plus). • 3+ years of experience on AWS (e.g., S3, Glue, EMR, Lambda, IAM, CloudWatch, MWAA/Airflow). • 2+ years of experience with infrastructure-as-code and CI/CD practices (Terraform preferred). • 2+ years of experience with Spark; streaming experience with Kafka is a plus. • Experience leveraging AI tools (e.g., GenAI assistants) to improve productivity, with an understanding of secure and responsible usage. The Ideal Qualifications • Self-driven, delivery-focused, and comfortable working in a contract environment with clear milestones and timelines. • Curious and methodical—able to research new data sources, open-source tools, and ingestion patterns to propose practical approaches. • Strong operational mindset: observability, alerting, incident response, and continuous improvement to reduce pipeline failures. • Clear communicator with strong stakeholder management skills; able to surface risks early and provide crisp status updates. • Familiarity with domain areas such as Portfolio Management, Cyber Security, and ServiceNow reporting is a plus.
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
Job Title: Data Engineer
We are looking for a Data Engineer to join our team and take ownership of our data infrastructure. You will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.Key Responsibilities
Pipeline Development: Create and maintain optimal data pipeline architecture (ETL/ELT) using tools like Airflow, DBT, or Fivetran.
Data Modeling: Design, build, and manage large, complex data sets that meet functional and non-functional business requirements.
Infrastructure Management: Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability.
Stakeholder Support: Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and GCP ‘big data’ technologies.
Data Quality: Work with data and analytics experts to strive for greater functionality in our data systems, ensuring data integrity and security.
Required Skills & Qualifications
Advanced SQL Knowledge: Experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
Programming: Proficiency in Python, Scala, or Java
Cloud Platforms: Experience with any cloud services such as AWS (Redshift, S3, Glue), Azure (Data Factory, Synapse), but preference for experience with Google Cloud (BigQuery).
Big Data Tools: Experience with Spark, Hadoop, Kafka, or similar distributed systems.
Data Warehousing: Solid understanding of Snowflake, Databricks, or similar modern data stack components.
Preferred Attributes
Experience supporting and working with cross-functional teams in a dynamic environment.
A "DevOps" mindset—experience with Docker, Kubernetes, and CI/CD pipelines.
Strong analytical skills related to working with unstructured datasets.
Responsibilities
Salary : Rs. 24,00,000.0 - Rs. 28,00,000.0
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
1. Program Delivery & Execution
• Own end-to-end delivery of large, complex technology programs from initiation to production rollout.
• Drive planning, estimation, execution, and governance across multiple projects.
• Ensure delivery within timelines, budget, and quality benchmarks.
• Establish and track KPIs, milestones, and program health metrics.
2. Stakeholder & Governance Management
• Engage with senior stakeholders, including EXCO and business heads, to align priorities and provide visibility on program status.
• Lead governance forums, steering committees, and executive reviews.
• Drive structured reporting on progress, risks, and dependencies.
3. Technology Leadership & Strategy
• Contribute to technology roadmap and strategic initiatives aligned to enterprise goals.
• Ensure adherence to enterprise architecture, security, and compliance standards.
• Guide adoption of modern engineering practices (API-led, cloud, DevSecOps).
4. Risk & Issue Management
• Proactively identify and manage risks, dependencies, and bottlenecks.
• Define mitigation plans and ensure timely resolution.
• Escalate critical risks with clear impact and resolution path.
5. Delivery Excellence & Process Improvement
• Drive adoption of Agile / Hybrid delivery models and best practices.
• Continuously enhance delivery frameworks, tools, and processes.
• Ensure effective SDLC governance, testing, and release management disciplines.
6. Financial & Resource Management
• Oversee program budgets, forecasts, and cost optimization.
• Align resource planning with program needs across internal teams and vendors.
• Track and report financial performance and variances.
7. Team Leadership & Capability Building
• Lead and mentor program managers, project managers, and engineering leads.
• Drive a high-performance, ownership-driven culture.
• Enable capability building across Agile, DevOps, and program governance.
Responsibilities
1. Program Delivery & Execution
• Own end-to-end delivery of large, complex technology programs from initiation to production rollout.
• Drive planning, estimation, execution, and governance across multiple projects.
• Ensure delivery within timelines, budget, and quality benchmarks.
• Establish and track KPIs, milestones, and program health metrics.
2. Stakeholder & Governance Management
• Engage with senior stakeholders, including EXCO and business heads, to align priorities and provide visibility on program status.
• Lead governance forums, steering committees, and executive reviews.
• Drive structured reporting on progress, risks, and dependencies.
3. Technology Leadership & Strategy
• Contribute to technology roadmap and strategic initiatives aligned to enterprise goals.
• Ensure adherence to enterprise architecture, security, and compliance standards.
• Guide adoption of modern engineering practices (API-led, cloud, DevSecOps).
4. Risk & Issue Management
• Proactively identify and manage risks, dependencies, and bottlenecks.
• Define mitigation plans and ensure timely resolution.
• Escalate critical risks with clear impact and resolution path.
5. Delivery Excellence & Process Improvement
• Drive adoption of Agile / Hybrid delivery models and best practices.
• Continuously enhance delivery frameworks, tools, and processes.
• Ensure effective SDLC governance, testing, and release management disciplines.
6. Financial & Resource Management
• Oversee program budgets, forecasts, and cost optimization.
• Align resource planning with program needs across internal teams and vendors.
• Track and report financial performance and variances.
7. Team Leadership & Capability Building
• Lead and mentor program managers, project managers, and engineering leads.
• Drive a high-performance, ownership-driven culture.
• Enable capability building across Agile, DevOps, and program governance.
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
Design and build Agentic AI workflows and autonomous agents using frameworks like LangChain, LlamaIndex, AutoGen, or CrewAI. Develop RAG?based solutions, including embeddings, vector search, retrieval pipelines, and context orchestration. Build multi-agent systems for planning, reasoning, decision-making, and tool use. Integrate LLMs (GPT, Azure OpenAI, Llama, Gemini) with backend apps, APIs, and enterprise systems. Create and optimize prompt templates, chains, copilots, and action functions. Implement LLM orchestration, reasoning loops, memory handling, and workflow automation. Ensure output quality using evaluation tools: RAGAS, DeepEval, LangSmith, TruLens. Apply guardrails for safety, bias mitigation, hallucination control, and compliance. Monitor model performance, drift, latency, and cost efficiency. Collaborate with product, ML, and engineering teams to build scalable GenAI solutions.
Responsibilities
Design and build Agentic AI workflows and autonomous agents using frameworks like LangChain, LlamaIndex, AutoGen, or CrewAI. Develop RAG?based solutions, including embeddings, vector search, retrieval pipelines, and context orchestration. Build multi-agent systems for planning, reasoning, decision-making, and tool use. Integrate LLMs (GPT, Azure OpenAI, Llama, Gemini) with backend apps, APIs, and enterprise systems. Create and optimize prompt templates, chains, copilots, and action functions. Implement LLM orchestration, reasoning loops, memory handling, and workflow automation. Ensure output quality using evaluation tools: RAGAS, DeepEval, LangSmith, TruLens. Apply guardrails for safety, bias mitigation, hallucination control, and compliance. Monitor model performance, drift, latency, and cost efficiency. Collaborate with product, ML, and engineering teams to build scalable GenAI solutions.
Salary : As per industry standard.
Industry :IT-Software / Software Services
Functional Area : IT Software - Application Programming , Maintenance
