Sougandhika Tera
Data Engineer
Summary
Data Engineer with 4+ years of experience designing scalable data pipelines, optimizing ETL/ELT workflows, and supporting analytics platforms across manufacturing (Filtrona), pharma (Novo Nordisk), and e-commerce/IoT (ACS). Strong hands-on expertise in SQL, Python, Scala/Java, Spark, AWS, Snowflake, Hadoop, Kafka, and orchestration tools like Airflow and ADF/Fabric. Experienced in Lakehouse architectures, CDC pipelines, real-time streaming, batch processing, and data modeling. Familiar with AI models/tools and application-integrated data flows. Adept at collaborating with business, engineering, and analytics teams to deliver high-quality, reliable data solutions in fast-paced environments.
Overview
4
4
years of professional experience
3
3
Certifications
Work History
Data Engineer
Filtrona
12.2024 - Current
- Designed enterprise-grade ELT pipelines using Fabric Data Pipelines & Lakehouse SQL for operations, quality, and manufacturing analytics.
- Built star schemas & semantic models for shop-floor insights, downtime analysis, batch tracking & OEE reporting.
- Implemented dbt-style SQL transformations with incremental logic, SCD handling & validation rules.
- Optimized query performance using partitioning, clustering & delta optimization.
- Created Power BI dashboards for production KPIs, waste trends, and equipment efficiency.
- Added audit logging, pipeline observability & custom error-handling for Fabric workflows.
- Built scalable ML data pipelines using ADF to automate feature extraction, model deployment triggers, monitoring, and feedback loops, ensuring reliable CI/CD workflows for ML models.
- Documented data flows, KPIs, data dictionary, lineage, and training materials for business users.
- Remote, USA. Environment: Microsoft Fabric, Lakehouse, SQL Endpoint, Spark, Delta tables, Power BI, ADF, Azure DevOps, Python.
AWS Data Engineer
Novo Nordisk Pharmaceuticals
NC
12.2022 - 10.2024
- Developed and maintained large-scale ETL/ELT pipelines extracting clinical & manufacturing datasets from SAP, Oracle, and LIMS systems into AWS and Snowflake.
- Built PySpark jobs for transforming raw clinical trial data, enforcing validation rules & audit checkpoints.
- Implemented CDC pipelines using DMS for near-real-time replication of LIMS and manufacturing systems.
- Designed star/snowflake schemas for analytical marts supporting regulatory, product quality, and supply chain reporting.
- Used Airflow to orchestrate pipelines with SLA monitoring, retries, email alerts & lineage metadata.
- Optimized AWS Glue jobs using partitioning, bucketing & predicate pushdown improving run time by 40%.
- Integrated Kafka streaming for ingesting IoT sensor data from manufacturing lines, enabling real-time alerts.
- Collaborated with data scientists to deliver clean feature datasets for ML models predicting batch deviations.
- NC, USA. Environment: AWS (Glue, S3, Lambda, Redshift, EMR), Snowflake, Kafka, Airflow, Python, Spark.
Data Engineer
ACS Technologies
India
05.2021 - 12.2021
- Designed ingestion pipelines to process e-commerce clickstream & cart events using Kafka → Spark → Snowflake.
- Developed PySpark transformations to enrich behavioral data with customer profiles for personalization workflows.
- Built ETL pipelines to migrate legacy datasets to Snowflake for faster analytics.
- Created Power BI dashboards for user journeys (add-to-cart, abandonment, trending products, exit-risk modeling).
- Automated pipeline deployments using Git, CI/CD, and parameterized ADF pipelines.
- Improved system reliability through data validation frameworks, error logging & SLA monitoring.
- India. Environment: AWS, Kafka, Spark, MySQL, Snowflake, Python, ADF.
Education
M.S. - Computer Information Systems
01.2023
B.Tech - Electronics & Communication Engineering
01.2021
Certification
- AWS Certified Cloud Practitioner
- AWS Certified Data Engineer – Associate
- Microsoft Certified Azure Fundamentals
- Introduction to Data Engineer by IBM (Coursera)
- Machine Learning Specialization (Coursera)
Skills
- Python
- Java (Basic)
- SQL
- Scala
- Apache Spark
- PySpark
- Hadoop
- Hive
- Kafka
- Airflow
- EMR
- Databricks
- AWS
- Azure
- Microsoft Fabric
- Snowflake
- Redshift
- MySQL
- SQL Server
- Oracle
- BigQuery
- AWS Glue
- Informatica
- ADF
- Fabric Pipelines
- Star/Snowflake schema
- Dimensional modeling
- Semantic modeling
- Git
- GitHub Actions
- Azure DevOps
- Docker
- Linux
- Jenkins
- Power BI
- Tableau
Publications
- Overcoming Early-Stage Adoption Challenges of Microsoft Fabric in Enterprise Environments (https://doi.org/10.63282/3050-9416.IJAIBDCMS-V6I4P108)
- The AI-Augmented Data Engineer: How LLMs and Copilots are Redefining the Engineering Workflow (https://doi.org/10.63282/3050-9246/ICRTCSIT-116)
- ENHANCED OCCUPANCY DETECTION SYSTEM USING ULTRASONIC/PIR SENSORS: IMPROVING ACCURACY AND EFFICIENCY IN SMART ENVIRONMENTS (https://pesjournal.net/paper.php?id=653)