Senior Software Developer

Tecsys; Bengaluru; On-site; INR 2,500,000 - 4,200,000; Full time

Benefits offered by this job

Competitive compensation packages

Career growth opportunities

Equal opportunity employer

Job summary

Tecsys Bengaluru is seeking a Senior Data Engineer to design, build, and evolve scalable data pipelines, data models, and data products on our analytics platform. You will transform structured, semi-structured, and unstructured data into AI-ready datasets to support Search, Recommendations, Marketing, and Supply Chain analytics with a focus on production-grade delivery.

The role requires hands-on expertise in Databricks and Spark, SQL and Python, and experience building reliable batch-first

Qualifications

• Advanced SQL and Python with focus on large-scale data processing.
• Hands-on Databricks, Spark and distributed processing experience.
• ETL/ELT pipeline design and workflow orchestration expertise.
• Data lakes/lakehouse architectures, partitioning and performance tuning.
• Data modeling including fact/dimension, SCDs and CDC pipelines.
• Experience with streaming architectures (Kafka, Pub/Sub, Kinesis) alongside batch.
• Ability to translate business needs into production-grade data solutions.

Responsibilities

• Design, build and evolve scalable data pipelines and data products on analytics platform.
• Develop datasets, feature layers, and semantic abstractions for AI/ML consumption.
• Implement ingestion, transformation and serving layers across Lakehouse architectures.
• Maintain robust data models and ensure data quality and governance.
• Collaborate with Product, Analytics, and Data Science teams; mentor engineers.
• Drive reliability, observability and incident response across data systems.

Skills

SQL & Python

Databricks/Spark

ETL/ELT pipelines

Data modeling

Data lakehouse concepts

Data quality & governance

ML/AI data prep

Education

Bachelor's or Master's in Computer Science/Engineering or related field

Tools

Airflow/Dagster

Kafka/ Pub/Sub / Kinesis

Docker & Kubernetes

CI/CD tooling

Snowflake / BigQuery / Redshift

Job description

About us

Tecsys is a global supply chain technology company that helps organizations achieve operational excellence through smarter supply chains. With a strong customer base across healthcare, retail, distribution, and complex logistics, we continue to grow our global footprint—and we’re excited to expand our team in India.

Earlier this year, we established Tecsys Supply Chain Solutions PVT Limited in Bangalore, further strengthening our global presence. This office builds on our existing India-based support capabilities by introducing new roles and functions that are critical to our 24/7 "follow the sun" global support model. This approach allows us to better serve customers across time zones while ensuring a balanced workload for our teams around the world.

Our growing India team plays a key role in supporting and enhancing our solutions, contributing to service delivery, innovation, and the ongoing success of some of the world’s most respected brands.

Position Overview

We are seeking a Senior Data Engineer to design, build, and evolve scalable data pipelines, data models, and data products on our analytics platform. This role focuses on building reliable, batch-first ETL/ELT systems on Databricks and Spark that transform structured, semi-structured, and unstructured data into high-quality, AI-consumable datasets—supporting Search, Recommendations, Marketing, and Supply Chain analytics. The ideal candidate is a hands‑on engineer who can translate ambiguous business needs into production‑grade data solutions, drive engineering best practices, and mentor peers while collaborating with architects, data scientists, and product teams.

Key Responsibilities

Data Pipeline & Platform Development

• Design, build, and maintain scalable ETL/ELT pipelines that ingest and transform structured, semi-structured, and unstructured data
• Develop high-fidelity data pipelines on Databricks/Spark optimized for reliability, cost, performance, and data freshness
• Build curated datasets, embeddings‑ready data, feature layers, and semantic abstractions that are AI/ML‑consumable for downstream systems
• Implement ingestion, transformation, and serving layers across Data Lake / Lakehouse architectures with a focus on efficient retrieval and contextual usability

Data Modeling & Architecture

• Develop and maintain robust data models including fact/dimension models, SCDs, wide tables, and CDC pipelines
• Apply data versioning, incremental processing, partitioning, and clustering strategies to ensure consistency, reproducibility, and cost efficiency
• Contribute to architectural decisions and trade‑offs across storage, compute, and orchestration layers within the analytics platform
• Help define and uphold data modeling standards, data contracts, and quality frameworks across teams

Analytics, AI & ML Enablement

• Prepare high-quality datasets for ML model consumption, feature engineering workflows, and predictive/forecasting use cases
• Contribute to a unified semantic layer that standardizes metrics, reusable definitions, and improves data access patterns
• Partner with Data Science teams to operationalize feature pipelines and support model training, serving, and monitoring

Quality, Governance & Reliability

• Implement data quality checks, contracts, and observability to ensure SLA/SLO adherence across pipelines
• Work with metadata, lineage, and data discovery frameworks to improve transparency, governance, and trust in data
• Drive improvements in pipeline reliability, monitoring, and incident response across the data ecosystem

Collaboration & Technical Leadership

• Partner cross‑functionally with Product, Analytics, and Data Science to translate ambiguous business problems into reusable data assets
• Mentor junior engineers, review code/designs, and raise the bar for engineering quality and best practices
• Communicate technical decisions, trade‑offs, and system designs clearly to both technical and non‑technical stakeholders

Required Skills & Experience

Technical Skills

• Advanced proficiency in SQL and Python, with strong focus on query optimization, cost efficiency, and large‑scale data processing
• Hands‑on experience with Databricks, Apache Spark, and distributed processing frameworks
• Strong experience building ETL/ELT pipelines and workflow orchestration (Airflow, Dagster, or similar)
• Solid understanding of Data Lake / Lakehouse architectures, storage formats (Parquet, Delta/Iceberg), partitioning, clustering, and performance tuning
• Deep expertise in data modeling: fact/dimension models, SCDs, wide tables, CDC, data versioning, and incremental processing
• Experience with event‑driven and streaming architectures (Kafka, Pub/Sub, Kinesis) applied pragmatically alongside batch where needed

Cloud & DevOps

• Hands‑on experience with at least one major cloud platform (AWS, Azure, or GCP) and cloud data warehouses (Snowflake, BigQuery, Redshift)
• Familiarity with Docker, Kubernetes, CI/CD pipelines, and infrastructure‑as‑code for data systems

Reliability, Observability & Governance

• Experience building production‑grade data systems with strong data quality, observability, and SLA/SLO practices
• Familiarity with metadata management, data lineage, and data discovery tools (e.g., DataHub, OpenMetadata, Amundsen)

Preferred

• Experience enabling AI/ML use cases from a data perspective — preparing datasets, feature stores, embeddings, or semantic/metric layers (dbt, Cube, LookML)
• Exposure to BI tools (Power BI, Tableau, Looker) and KPI modeling for business stakeholders
• Experience in Supply Chain, Logistics, or Healthcare supply chain analytics
• Familiarity with domains such as Search, Recommendations, or Marketing analytics

Soft Skills

• Proven ability to translate ambiguous business requirements into scalable data models and systems
• Ownership mindset — drives features end‑to‑end with strong communication and collaboration skills

Qualifications

• Bachelor's or Master's in Computer Science, Engineering, or related field — or equivalent practical experience
• 6–8+ years of experience in Data Engineering, building and operating production‑grade data platforms at scale
• Demonstrated experience delivering data solutions across analytics, ML, or product‑facing domains

This role will require you to be based in Bengaluru.

At Tecsys, we value creativity, innovation, and teamwork. Our employees enjoy a supportive work environment, competitive compensation packages, and opportunities for career growth and advancement.

Tecsys is an equal opportunity employer.