Daniel Abraham R

Data Engineer

Chennai, Tamil Nadu, India3 yrs 9 mos experience

Key Highlights

Expert in building scalable ETL frameworks.
Proficient in multiple Big Data technologies.
Strong command over AWS services for data solutions.

Stackforce AI infers this person is a Data Engineering specialist with expertise in scalable ETL processes and cloud technologies.

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Skills

Core Skills

Data EngineeringAwsEtl

Other Skills

Data Build Tool (DBT)PySparkApache AirflowAmazon Web Services (AWS)AWS AthenaDBTHadoopAWS S3AWS Managed Workflows for Apache AirflowGoogle Cloud Platform (GCP)Quality Assurance TestingData ArchivingData Warehouse ArchitectureData CleaningData Modeling

About

Dexterous Data Engineer with 3 years experience. Designed a number of OpenSource frameworks perform the ETL processes and making it highly scalable to use in all industries easing up the work to perform the ETL operations. Got great exposure on different Big Data Frameworks (Hadoop, Hive, PySpark, Spark SQL, Kafka, Spark Streaming), Databases (MySQL, Oracle, Redshift, MongoDB, Postgres), AWS Services (S3, EMR, Glue, Athena, KMS, SNS, SQS, MWAA, Cloudwatch), Workflow Managers (Apache Airflow), good command over programming languages (Python, Java, JavaScript) and adroit in Data Structures and Algorithms. Learning about data in this data driven world is always refreshing and astounding because of its importance in our day to day life and how it should be handled and safeguarded.

Experience

3 yrs 9 mos

Total Experience

2 yrs 11 mos

Average Tenure

10 mos

Current Experience

Deloitte

Data Engineer - Consultant

Jul 2025 – Present · 10 mos · Chennai, Tamil Nadu, India · Hybrid

Data Build Tool (DBT)PySparkApache AirflowAmazon Web Services (AWS)Data EngineeringAWS

Tata consultancy services

4 roles

Data Engineer II

Mar 2025 – Jul 2025 · 4 mos · On-site

Data Engineer II

Feb 2025 – Mar 2025 · 1 mo · On-site

Junior Data Engineer

Promoted

Jun 2023 – Feb 2025 · 1 yr 8 mos · On-site

1. Automated reporting pipelines leveraging AWS Athena for query execution and Apache Airflow for orchestration, reducing manual intervention by 40% and enabling near real-time insights.
2. Achieved a 30% improvement in data processing latency and a 20% increase in data accuracy by optimizing ETL processes and enhancing analytical workflows.
3. Developed robust data transformation pipelines with DBT, implementing modular and version-controlled SQL workflows that improved query performance and ensured data consistency across environments.
4. Implemented metric monitoring and workflow optimization strategies, enhancing system reliability and throughput by 25% through detailed performance analysis and resource tuning.
5. Partnered with cross-functional teams to design and deploy scalable, enterprise-grade data solutions, driving a 30% improvement in operational efficiency through streamlined processes and automation.

AWS AthenaApache AirflowETLDBTData Engineering

Junior Data Engineer

Jul 2022 – Jun 2023 · 11 mos · On-site

1. Engineered PySpark and Hadoop-based ingestion frameworks to process over 1TB of data daily, enabling efficient multi-format storage (JSON, Parquet, Avro) in AWS S3.
2. Migrated to open-source technologies, eliminating proprietary dependencies, reducing licensing expenses by 60%, and implementing cost-efficient AWS S3 storage policies.
3. Optimized ETL workflows using AWS Managed Workflows for Apache Airflow (MWAA), reducing cloud infrastructure overhead by 24% through improved resource allocation and task orchestration.
4. Implemented Medallion Architecture for layered data organization, achieving a 20% boost in data
quality and processing throughput through optimized schema design and validation protocols.

PySparkHadoopAWS S3ETLApache AirflowData Engineering