Walk-in || Senior Data and Analytics Engineer

Senior Data & Analytics Engineer Job Description

Role Overview

The Senior Data & Analytics Engineer will be responsible for designing, building, optimizing, and governing scalable data platforms while enabling advanced analytics, business intelligence, and data-driven decision-making across the organization. The role combines strong Data Engineering expertise with hands-on Analytics and BI capabilities, requiring the candidate to build robust data pipelines, curate analytical datasets, develop dashboards, and deliver actionable business insights.

The ideal candidate will possess deep expertise in Databricks, SQL, PySpark, AWS, and modern analytics platforms, with experience handling large-scale datasets and collaborating closely with business stakeholders to transform data into measurable business outcomes.

Location: Bengaluru

Key Responsibilities

Data Engineering & Platform Development

• Design, develop, and maintain scalable data pipelines and ETL/ELT workflows using Databricks, PySpark, and SQL.
• Build reusable frameworks, templates, and engineering standards for batch, streaming, and near real-time data processing.
• Develop and maintain modern Lakehouse architectures leveraging Delta Lake and Unity Catalog.
• Design data models, solution architectures, and analytics-ready data assets.
• Implement orchestration and scheduling frameworks using Databricks Workflows and Airflow.
• Ensure cloud-native data solutions aligned with AWS best practices.
• Optimize data pipelines, SQL queries, and workloads for performance, scalability, and cost efficiency.

Data Analytics & Reporting

• Perform data extraction, transformation, validation, and advanced analytics using SQL, Python, and PySpark.
• Develop dashboards, scorecards, reports, and self-service analytical solutions using Power BI, Databricks AI/BI, or similar BI platforms.
• Conduct data reconciliation and validation activities to ensure reporting accuracy and consistency.
• Analyze large and complex datasets to identify trends, anomalies, opportunities, and actionable insights.
• Support ad-hoc business analysis and strategic initiatives through data-driven recommendations.
• Enable business stakeholders with timely, accurate, and consumable insights.

Stakeholder Collaboration

• Partner with business leaders, analysts, product teams, and technology stakeholders to understand requirements and translate them into scalable data solutions.
• Collaborate across engineering and analytics teams to deliver high-impact business outcomes.
• Support project estimation, solution design, and implementation planning for strategic initiatives.
• Support ad-hoc analysis for strategic initiatives
• Collaborate with cross-functional teams to streamline data processes, enhance data quality, and drive organizational efficiency.
• Provide training and support to end business users on data tools and techniques, empowering them to leverage data effectively

Optimization & Governance

• Ensure compliance with data governance and security standards.
• Ensure data reliability, integrity, observability, and monitoring across the data ecosystem.
• Maintain business glossaries, documentation, technical artifacts, and operational runbooks.
• Promote best practices around data quality, compliance, and platform governance.
• Optimize queries for performance and cost efficiency.

AI & Advanced Analytics (Preferred)

• Support adoption of AI/BI capabilities within Databricks.
• Contribute to GenAI, metadata enrichment, automated data quality, and analytical automation initiatives.
• Evaluate opportunities to leverage ML and AI technologies for enhanced business outcomes.

Required Skills & Experience

• 6-9 years of experience in Data Engineering, Analytics, Business Intelligence, or related fields.
• Strong hands-on expertise with:
• AWS services such as S3, Glue, Redshift, Lambda, and RDS
• Airflow, Databricks Workflows, Delta Lake and Unity Catalog
• Python, PySpark, and Spark SQL
• SQL and Data Modeling
• Power BI, Databricks AI/BI, or equivalent BI tools
• Experience handling large-scale datasets in distributed computing environments.
• Strong understanding of ETL/ELT design patterns and modern data architectures.
• Experience building analytical data models and reporting solutions.
• Knowledge of batch, streaming, and real-time processing frameworks.
• Strong analytical, problem-solving, and troubleshooting skills.
• Excellent verbal and written communication skills with experience engaging business stakeholders.
• Experience working within Agile delivery environments. (Good to have)
• Exposure to AI/ML, Model Serving, Vector Search, or GenAI solutions. (Good to have)
• Experience implementing data governance, metadata management, and observability frameworks. (Good to have)

Preferred Qualifications

• Databricks Certified Data Engineer Professional certification. (Good to have)
• AWS Data Analytics or related cloud certification. (Good to have)
• Any AI certification (Good to have)