Senior Data Engineer

de facto infotech; Sahibzada Ajit Singh Nagar; Híbrido; INR 2.000.000 - 4.000.000; Jornada completa

Descripción de la vacante

Defactoinfotech seeks a Senior Data & Analytics Engineer to design, develop, and optimize enterprise-scale data platforms and analytics solutions. The role blends data engineering, BI, and AI-ready analytics in a hybrid setup across on-prem and cloud environments.

The ideal candidate will model data, govern quality, and empower data-driven decisions by delivering scalable pipelines, dashboards, and governance across Azure/AWS/GCP stacks.

Formación

• Enterprise data engineering experience.
• Strong SQL & DB tuning skills.
• Experience with cloud data platforms (Azure/AWS/GCP).
• Data warehousing, dimensional modeling, and lakehouse concepts.
• Proficient in Power BI or Tableau for analytics.
• Programming with Python or PySpark.
• Experience with big data tools (Spark, Kafka).
• Knowledge of data governance and quality frameworks.
• Excellent stakeholder communication and collaboration.
• Experience in Agile or Hybrid delivery environments.

Responsabilidades

• Design and maintain scalable data pipelines (ETL/ELT).
• Build and optimize data warehouses and lakehouse architectures.
• Collaborate with stakeholders to define KPIs and translate needs.
• Develop data models, dictionaries, and governance frameworks.
• Analyze large datasets to identify trends and opportunities.
• Create dashboards and visualizations using BI tools.
• Monitor data pipeline performance, reliability, and security.
• Implement data validation and quality monitoring.

Conocimientos

SQL & DBT optimization

ETL/ELT tools

Cloud data platforms

Data modeling

BI tools

Python/PySpark

Big data tech

Data governance & quality

Stakeholder comms

Agile/Scrum

Educación

Bachelor's degree in CS/EE/Data

Herramientas

Azure Data Factory

Snowflake/BigQuery

Databricks

Power BI/Tableau

Hadoop/Kafka

Descripción del empleo

Overview

We are seeking a highly skilled Senior Data & Analytics Engineer to drive the design, development, and optimization of enterprise-scale data platforms and analytics solutions. This hybrid role requires expertise in data engineering, data modeling, business intelligence, and advanced analytics to transform complex data into actionable business insights. The ideal candidate will collaborate with business stakeholders, architects, and technology teams to build scalable data ecosystems, improve data quality, and enable data-driven decision-making while leveraging modern cloud and AI-powered technologies.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines, ETL/ELT processes, and data integration frameworks across multiple data sources.
• Build and optimize enterprise data warehouses, data lakes, and lakehouse architectures to support analytics and reporting requirements.
• Collaborate with business stakeholders to gather requirements, define KPIs, and translate business needs into data solutions.
• Develop data models, data dictionaries, and governance frameworks to ensure data consistency, quality, and compliance.
• Analyze large and complex datasets to identify trends, patterns, and business opportunities.
• Create and maintain interactive dashboards, reports, and visualizations using modern BI tools.
• Monitor and improve data pipeline performance, reliability, scalability, and security.
• Implement data validation, quality monitoring, and reconciliation processes across enterprise systems.
• Work closely with data scientists, business analysts, and application teams to support analytics and AI initiatives.
• Drive automation and optimization initiatives to improve operational efficiency and reporting accuracy.
• Support data migration, modernization, and cloud transformation programs.
• Mentor junior data engineers and analysts while promoting data engineering best practices.

Required Skills & Qualifications

• Strong experience designing and implementing enterprise data engineering and analytics solutions.
• Expertise in SQL and advanced database concepts, including query optimization, indexing, partitioning, and performance tuning.
• Hands-on experience with ETL/ELT tools such as Azure Data Factory, SSIS, Informatica, Talend, Matillion, or similar platforms.
• Strong experience with cloud data platforms including Azure, AWS, or Google Cloud.
• Proficiency in data warehousing concepts, dimensional modeling, star schemas, and data lake architectures.
• Experience working with structured, semi-structured, and unstructured datasets.
• Strong analytical skills with the ability to derive actionable insights from complex business data.
• Hands-on experience with Power BI, Tableau, Looker, Qlik, or other business intelligence tools.
• Knowledge of Python, PySpark, Scala, or similar technologies for data processing and automation.
• Experience with big data technologies such as Spark, Databricks, Hadoop, Kafka, or Snowflake.
• Strong understanding of data governance, master data management, metadata management, and data quality frameworks.
• Excellent communication, stakeholder management, and documentation skills.
• Experience working in Agile, Scrum, or hybrid project delivery environments.

Data Engineering Capabilities

• Design and maintain high-performance data pipelines supporting enterprise analytics workloads.
• Build scalable batch and real-time data processing solutions.
• Develop and optimize cloud-native data architectures and modern data platforms.
• Implement CI/CD practices for data engineering deployments and automation.
• Experience with API integrations, event-driven architectures, and streaming data solutions.
• Ensure data security, privacy, compliance, and governance standards are consistently maintained.
• Optimize data storage, processing costs, and system performance across cloud platforms.

Data Analytics & Business Intelligence Capabilities

• Gather business requirements and translate them into meaningful reporting and analytics solutions.
• Design executive dashboards and self-service reporting frameworks.
• Perform exploratory data analysis, trend analysis, forecasting, and KPI development.
• Deliver actionable insights that support strategic business decisions and operational improvements.
• Create data storytelling presentations and executive-level reporting artifacts.
• Collaborate with cross-functional teams to identify opportunities for business process optimization through data.

AI & Modern Data Platform Capabilities

• Experience supporting AI, Machine Learning, and Advanced Analytics initiatives through robust data engineering foundations.
• Familiarity with Azure AI, Azure OpenAI, Databricks AI, AWS AI/ML, or similar platforms.
• Experience preparing and managing datasets for predictive analytics, machine learning, and Generative AI use cases.
• Understanding of data requirements for AI model training, deployment, and monitoring.
• Knowledge of intelligent automation, data enrichment, and AI-powered analytics solutions.
• Ability to identify opportunities where AI and advanced analytics can improve business outcomes and operational efficiency.
• Understanding of responsible AI, data governance, security, and compliance considerations.

Preferred Qualifications

• Experience with Microsoft Azure Data Platform technologies including Azure Data Factory, Synapse Analytics, Azure Databricks, Fabric, and Data Lake Storage.
• Experience with Snowflake, Redshift, BigQuery, or other cloud-native data warehouses.
• Exposure to real-time analytics, streaming platforms, and event-driven architectures.
• Experience supporting enterprise reporting and analytics programs across multiple business functions.
• Knowledge of data governance frameworks and regulatory compliance requirements.
• Experience working with global or multi-region data platforms.
• Relevant certifications such as Microsoft Azure Data Engineer (DP-203), Microsoft Fabric Analytics Engineer (DP-600), AWS Data Analytics Specialty, Snowflake Certifications, Databricks Certifications, or equivalent.

Why You'll Love This Role

• Lead enterprise-scale data transformation and modernization initiatives.
• Work with cutting-edge cloud, analytics, and AI technologies.
• Collaborate with experienced architects, data professionals, and business leaders.
• Continuous learning opportunities through certifications and professional development programs.
• Exposure to diverse industries and large-scale data ecosystems.
• Opportunity to influence business strategy through data-driven insights and innovation.

Empower organizations to unlock the full value of their data through modern engineering, advanced analytics, and AI-driven innovation.