Data Engineer

Job Description:

Data Engineer (Streaming & Integration)

Position: Data Engineer (Streaming &

Integration)

Location: offshore/India

Experience: Minimum 8+ years

Role Overview

We are hiring one Data Engineer to lead the

design, development, and operation of

streaming and enterprise data pipelines.

This role owns technical direction, makes

architectural trade-offs, and works directly with

onsite clients in the US.

This is a builder + owner role. You will write

code, review designs, debug production issues,

and set engineering standards.

Responsibilities

• Architect, build, and operate real-time

and near-real-time data pipelines

• Lead development using Confluent

Kafka and Apache Flink

o Apache Spark Structured

Streaming is acceptable instead of

Flink

Required Skills & Experience:

• 8+ years of hands-on data engineering

experience

• Exceptional SQL skills (complex

analytics, performance tuning)

• Strong expertise in Python, Java, or .NET

(C#)

(at least one OOP language is mandatory)

• Deep experience with Confluent

Kafka (architecture, partitioning, delivery

semantics)

• Hands-on streaming experience with:

o Apache Flink (preferred) or

o Apache Spark Structured

Streaming

• Strong understanding of:

o ETL / ELT patterns

o MPP processing concepts

o Data modeling and orchestration

• Experience with SQL Server

• Good understanding of data governance,

secure PII handling within streaming data

pipelines.

• Experience with event serialization formats

like Protobuf / JSON Schema

Nice to Have

• SSIS experience

• Docker / Kubernetes

• Design and maintain batch and hybrid

ETL pipelines using SQL Server and

SSIS

• Own data quality, observability, and

reliability across pipelines

• Define and enforce best practices for:

o Streaming semantics

o Error handling

o Backpressure and performance tuning

• Work directly with onsite clients:

o Translate requirements into technical

solutions

o Defend design decisions

o Troubleshoot complex production

issues

• Mentor engineers and raise overall

engineering bar

• Collaborate with DevOps and platform

teams in containerized, distributed

environments

• Manage event schema registries and

backward compatibility standards across

streaming pipelines.

• Partner with downstream and upstream

system teams to define robust data

contracts and payloads.