Senior Data Engineer

Job Summary :

We are seeking an experienced

Data Engineer

with strong expertise in

AWS cloud services

and

Databricks

to design and implement scalable, high-performance data pipelines. The role involves building and optimizing ETL / ELT workflows, managing big data environments, and ensuring seamless data availability for analytics, AI / ML, and business intelligence use cases.

Key Responsibilities :

Design, develop, and maintain

data pipelines

and workflows using

AWS (S3, Redshift, Glue, EMR, Lambda, Kinesis, Athena)

and

Databricks .

Build and optimize

ETL / ELT processes

for large-scale structured and unstructured datasets.

Leverage

Databricks

for data engineering, advanced analytics, and machine learning workloads.

Collaborate with data scientists, analysts, and stakeholders to deliver reliable and scalable data solutions.

Implement

data governance, quality checks, and monitoring frameworks .

Ensure high availability, scalability, and cost-effectiveness of data solutions.

Required Skills :

7+ years of experience in

data engineering .

Strong hands-on experience with

AWS cloud services

(S3, Redshift, Glue, EMR, Athena, Lambda, Kinesis).

Expertise in

Databricks

(PySpark, Delta Lake, ML pipelines).

Proficiency in

Python

and

SQL

for data transformation and querying.

Strong understanding of

data warehousing, data modeling, and big data frameworks .

Experience with workflow orchestration tools (Airflow, Step Functions).

Preferred Qualifications :

Familiarity with

MLOps / ML integration

within Databricks.

Experience with

real-time / streaming data

(Kafka, Spark Streaming).

Knowledge of

infrastructure as code

(Terraform / CloudFormation).

Exposure to data security, compliance, and governance practices.